Dividing a Graphical Cake

Xiaohui Bei, Warut Suksompong

Introduction

Cake cutting refers to the problem of fairly allocating a divisible resource, often modeled as a cake, among agents with varying preferences. The problem dates back to shortly after the end of World War II (Steinhaus, 1948) and, not surprisingly given its wide range of applications, still enjoys significant attention in mathematics, computer science, economics, and political science to this day (Brams and Taylor, 1996; Robertson and Webb, 1998; Procaccia, 2016).

What does it mean for an allocation to be fair? Steinhaus (Steinhaus, 1948) proposed the following definition of fairness: if the cake is divided between nn agents, each agent should receive a part that she values at least 1/n1/n of the entire cake. This definition became known as proportionality, and is one of the most fundamental notions in the literature of fair division. In his seminal article, Steinhaus showed that a proportional allocation can be found for any number of agents with arbitrary preferences over the cake—Steinhaus’ method, which he attributed to Knaster and Banach, was later formulated as a moving-knife procedure by Dubins and Spanier (Dubins and Spanier, 1961). The procedure works by having a referee move a knife over the cake from left to right. Whenever the left part has value 1/n1/n of the entire cake for one of the agents, the agent takes that part of the cake and leaves; the procedure is then repeated among the remaining agents. In addition to ensuring proportionality, the Dubins-Spanier protocol has the important property that it always allocates to every agent a connected piece of the cake. Without this property, it may well be that an agent is presented with—in the words of Stromquist (Stromquist, 1980)—a “union of crumbs”.

The proportionality guarantee of the Dubins-Spanier protocol holds for a variety of items that one may wish to divide, since an item of any shape or form can be “projected” onto a line, which we can then run the protocol on. However, the connectivity property does not necessarily translate from the line back to the original shape. A simple illustrating example is when the item has the shape of a ring (e.g., a donut or a ring road): projecting the ring onto a line and applying Dubins-Spanier may result in an agent receiving disconnected pieces of the ring. For this example, the difficulty can be circumvented by cutting the ring at an arbitrary point, stretching it into a line, and running the protocol to achieve proportionality. Nevertheless, one may already begin to suspect that this type of fix no longer works when the shapes get more complex.

In this paper, we consider a natural setting where the cake is represented by the set of edges of an arbitrary undirected graph. The graph could correspond to a resource in the form of a network, such as a road or power cable network. The canonical cake-cutting setting, where the cake is assumed to be the interval $$, is a special case of our setting, with the graph consisting of a single edge. In this generalized graphical setting, we show that proportionality cannot always be attained if connectivity is required. Therefore, our goal in this work is to provide the best possible approximation of proportionality that can be achieved in each graph. As we will see, despite allowing arbitrary graphs and agents’ preferences in our model, we can still obtain several strong fairness guarantees. Furthermore, we study a number of variants and extensions, including when each agent can get more than one connected piece, or when the item to be divided is undesirable (often referred to as a chore).

We assume throughout the paper that the agents are endowed with valuation functions that are additive and normalized with each agent having value 11 for the whole cake; these assumptions are standard in the cake-cutting literature (Procaccia, 2016). We also assume that the pieces of cake that different agents receive may intersect in a finite number of points. Our formal model is described in Section 2.

In Section 3, we provide general guarantees that hold for any number of agents. For nn agents with arbitrary valuations and any graph, we establish the existence of a connected allocation that gives every agent a utility of at least 12n−1\frac{1}{2n-1}. We also show that this bound is tight even when the agents have identical valuations and the graph is a star with 2n−12n-1 edges. In addition, for every specific star graph, we determine the optimal utility that can be guaranteed for each number of agents.

In Section 4, we delve deeper into the case of two agents. While we know from Section 3 that both agents can be guaranteed a utility of 1/31/3 in general, for certain graphs it is possible to do better. Perhaps surprisingly, we show that the optimal guarantee for each graph is always either 1/31/3 or 1/21/2; the latter case corresponds to a proportional allocation. The classification depends on a graph property that we call almost bridgeless—a graph satisfies this property if we can add an edge so that the resulting graph contains no bridges, where a bridge refers to an edge that is not contained in any cycle. We show that a guarantee of 1/21/2 can be obtained if the graph is almost bridgeless, while 1/31/3 is the best possible guarantee otherwise.

Next, we strengthen the result that both agents can be guaranteed a utility of 1/31/3 for any graph by establishing the existence of a connected allocation such that the first agent receives value at least 1/21/2 and the second agent at least 1/31/3. More generally, we characterize all pairs (α,β)(\alpha,\beta) for which there always exists a connected allocation that yields utility at least α\alpha and β\beta to the first and second agent, respectively. On the other hand, if we are only interested in giving utility α\alpha to one agent and β\beta to the other, and are willing to give up control over which agent receives which guarantee, then additional pairs (α,β)(\alpha,\beta) become achievable—again, we give a complete characterization of all such pairs. Moreover, we consider allocating more than one connected piece to each agent: we show that for any positive integer kk, both agents can be guaranteed a utility of 12−12⋅3k\frac{1}{2}-\frac{1}{2\cdot 3^{k}} if we allow the agents to receive a total of k+1k+1 connected pieces, and this is tight. We also study approximate equitability and prove the existence of a connected allocation for which the agents’ utilities differ by no more than 1/31/3; we again establish the tightness of the bound.

Finally, in Section 5, we turn our attention to chore division. In the case of two agents there is a simple reduction between the settings of cake and chores, so all of our results in Section 4 carry over to chore division. By contrast, when there are more than two agents, the relationship between the two settings is much less clear. We show that there exists a connected allocation that incurs cost at most 2n+1\frac{2}{n+1} for n≤5n\leq 5, and that no better bound can be obtained for any nn.

We remark that all of our positive results are constructive: for each result, we exhibit a moving-knife protocol that achieves the desired guarantee. Moreover, one can make these protocols discrete, so that they only use the cut and evaluation queries allowed by the Robertson-Webb query model in order to access the valuation functions of the agents (Robertson and Webb, 1998).

2. Further Related Work

While our graphical cake model is new to the best of our knowledge, graphs have recently been studied in the context of allocating indivisible items. In particular, the items correspond to vertices of an undirected graph, and each agent must be allocated a connected subgraph of the graph. A line of work has explored existence and complexity questions for several fairness notions, both in the case of goods (Bouveret et al., 2017; Lonc and Truszczynski, 2018; Bilò et al., 2019; Bei et al., 2019; Igarashi and Peters, 2019; Suksompong, 2019) and chores (Bouveret et al., 2019).

Connectivity constraints are commonly considered in the cake-cutting literature, where each agent is allocated a single subinterval of the interval cake (Stromquist, 1980, 2008; Su, 1999; Bei et al., 2012; Cechlárová and Pillárová, 2012; Aumann et al., 2013; Cechlárová et al., 2013; Aumann and Dombb, 2015; Segal-Halevi et al., 2016). Segal-Halevi et al. (Segal-Halevi et al., 2017) studied the fair division of land and introduced geometric constraints to the setting by requiring that allocated pieces be of certain shape—such requirements are important since a long but narrow piece of land is likely to be of little practical use. Similarly to our setting, a proportional allocation does not always exist in the presence of these constraints, and the authors examined the approximations of proportionality that can be obtained.

Preliminaries

Let N={1,2,…,n}N=\{1,2,\dots,n\} be the set of agents, and G=(V,E)G=(V,E) be a finite and connected undirected graph representing the cake, with no loops but possibly with multiple edges joining the same pair of vertices.A loop can be represented in our model by adding a new vertex inside the loop, thereby breaking the loop into two edges joining the same pair of vertices. Denote by mm the number of edges. Each edge in EE can be viewed as an interval of the cake. For any points x,yx,y on an edge, we write [x,y][x,y] or [y,x][y,x] to denote the interval of the cake between xx and yy; we sometimes identify a vertex v∈Vv\in V with the corresponding endpoint of the edges adjacent to vv.

A piece of cake is a finite union of disjoint intervals, where each interval is a subinterval of an edge and the intervals in the piece may belong to different edges.As is commonly done in cake cutting, we assume that all intervals are closed intervals. Two intervals are said to be disjoint if they intersect in at most one point, and two pieces of cake are said to be disjoint if they intersect in a finite number of points. If we adopt the stricter convention that each point can only be allocated to one agent (so intervals can be open, half-open, or closed) and two intervals are disjoint only if their intersection is empty, there are strong negative results. For example, on a star graph, at most one agent would be able to receive intervals from more than one branch in a connected allocation. A piece of cake is said to be connected if for any two points in the piece, it is possible to get from one point to the other along the graph GG by only traversing this piece of cake. Each agent ii has a nonnegative valuation function (or utility function) fif_{i}, which specifies the agent’s value for each piece of cake. An instance consists of the graph GG, the agents, and their valuation functions. As is standard in the cake-cutting literature (Procaccia, 2016), we assume that the valuation functions are

normalized: the value of an agent for the entire cake is 11;

divisible: for each interval [x,y][x,y] and 0≤λ≤10\leq\lambda\leq 1, there is a point z∈[x,y]z\in[x,y] such that fi([x,z])=λ⋅fi([x,y])f_{i}([x,z])=\lambda\cdot f_{i}([x,y]);

additive: the value of an agent for a piece of cake is the sum of her values for the intervals in the piece.

An allocation of the cake is denoted by a vector A=(A1,…,An)A=(A_{1},\dots,A_{n}), where each AiA_{i} is a piece of cake, and AiA_{i} and AjA_{j} are disjoint for all i≠ji\neq j. An allocation is said to be complete if the entire cake is allocated, and connected if each AiA_{i} is a connected piece of cake. The egalitarian welfare of an allocation is defined as min⁡i∈Nfi(Ai)\min_{i\in N}f_{i}(A_{i}). An allocation is proportional if its egalitarian welfare is at least 1/n1/n. The inequity of an allocation is defined as max⁡i,j∈N∣fi(Ai)−fj(Aj)∣\max_{i,j\in N}|f_{i}(A_{i})-f_{j}(A_{j})|; an allocation with inequity is said to be equitable.

We make analogous assumptions for chore division (Section 5). Each agent has a nonnegative cost function fif_{i} for the chore, which is normalized, divisible, and additive. The egalitarian cost of an allocation is defined as max⁡i∈Nfi(Ai)\max_{i\in N}f_{i}(A_{i}). Naturally, we require the entire chore to be allocated, so we restrict our attention to complete allocations of the chore.

Any Number of Agents

In this section, we present an egalitarian welfare guarantee that holds for any number of agents and arbitrary graphs, and derive improved guarantees in the case where the graph is a star.

We begin by showing that it is always possible to give every agent a utility of at least 12n−1\frac{1}{2n-1}, and this bound is tight. Similarly to the Dubins-Spanier protocol, our algorithm proceeds by identifying a piece that is valuable enough for one agent but at the same time not too valuable for the other agents, allocating such a piece to the former agent, and recursing on the latter agents.

For any graph GG, there exists a connected allocation with egalitarian welfare at least 12n−1\frac{1}{2n-1}. On the other hand, there exists a graph GG and identical valuations of the agents such that any connected allocation yields egalitarian welfare at most 12n−1\frac{1}{2n-1}.

Let α:=12n−1\alpha:=\frac{1}{2n-1}. To show the second part of the theorem, let GG be a star with 2n−12n-1 edges such that every agent values each edge exactly α\alpha, and the value is distributed uniformly within the edge. Assume for contradiction that there is a connected allocation with egalitarian welfare strictly greater than α\alpha. Consider any agent ii. The agent must receive intervals from at least two edges, and these intervals must be connected via the center vertex. Note that the unallocated parts of these edges cannot be allocated to other agents, since any agent who receives an interval from such a part cannot receive intervals from other edges and would therefore obtain value less than α\alpha. Hence, at least two edges are only allocated to agent ii. However, this means that there must be at least 2n2n edges in total, a contradiction.

We now prove the first part of the theorem. Let GG be an arbitrary graph. We will show that there exists a moving-knife algorithm that produces a connected allocation with egalitarian welfare at least α\alpha. We proceed by induction on nn; the statement trivially holds for n=1n=1 since we can simply allocate the entire cake to the only agent. Assume that the statement holds for n−1n-1 agents, and consider an instance with nn agents.

First, we claim that we can turn GG into a tree. As long as GG contains at least one cycle, pick an edge uvuv that belongs to a cycle, add a new vertex v′v^{\prime}, and replace this edge by an edge uv′uv^{\prime} while keeping the remaining edges of the graph as before. Since at least one cycle is removed by this operation and no new cycle is created, GG eventually becomes a tree. Note that any connected allocation of the modified graph is a connected allocation in the original graph with the same value for every agent, so it suffices to prove the theorem for the modified graph.

Choose an arbitrary vertex uu of the tree GG as its root. Let vv be a vertex such that the subtree rooted at vv yields value at least α\alpha to some agent, and the same does not hold for the subtree rooted at any child of vv. Let w1,…,wkw_{1},\dots,w_{k} be the children of vv. We consider two cases:

Case 1: At least one of the kk branches of vv along with the corresponding subtree yields value at least α\alpha to some agent. Assume without loss of generality that the branch containing w1w_{1} is one such branch. By our assumption, the subtree rooted at w1w_{1} yields value less than α\alpha to all agents. Hence, by moving a knife from w1w_{1} to vv, we can find the point xx closest to w1w_{1} such that some agent ii values the interval [w1,x][w_{1},x] together with the subtree rooted at w1w_{1} exactly α\alpha, and all other agents value this piece of cake at most α\alpha. We allocate this piece of cake to agent ii, and make xx a new vertex in the remaining graph, which has value at least 1−α1-\alpha for each of the remaining agents. By the inductive hypothesis, there exists a connected allocation of the remaining graph to the n−1n-1 agents such that every agent receives value at least 12n−3⋅(1−α)=12n−3⋅2n−22n−1>α\frac{1}{2n-3}\cdot(1-\alpha)=\frac{1}{2n-3}\cdot\frac{2n-2}{2n-1}>\alpha, as desired.

Case 2: Every branch of vv along with the corresponding subtree yields value less than α\alpha to all agents. Let t∈{1,2,…,k}t\in\{1,2,\dots,k\} be the smallest number such that the first tt branches and their subtrees together yield value at least α\alpha to some agent ii. We allocate this piece of cake to agent ii. For every other agent, the first t−1t-1 branches is worth less than α\alpha and the ttth branch is also worth less than α\alpha, so the piece of cake allocated to agent ii is worth less than 2α2\alpha. By the inductive hypothesis, there exists a connected allocation of the remaining graph to the n−1n-1 agents such that every agent receives value at least 12n−3⋅(1−2α)=12n−1=α\frac{1}{2n-3}\cdot(1-2\alpha)=\frac{1}{2n-1}=\alpha, as desired.

The two cases together complete the induction. ∎

Note that by following the algorithm in the proof of Theorem 3.1, we also obtain the following statement, which will be useful for our later results.

Let HH be a connected piece of cake in a graph GG, and suppose that all agents have value xx for HH. For any α≤x\alpha\leq x, there exists a partition of HH into two connected pieces such that one of the agents has value at least α\alpha for the first piece, while all of the remaining agents have value at most 2α2\alpha for this piece.

2. Stars

For certain graphs, it is possible to improve upon the guarantee provided by Theorem 3.1—an obvious example is the graph consisting of a single edge, for which the Dubins-Spanier protocol yields an egalitarian welfare of at least 1/n1/n. We now derive the optimal egalitarian welfare guarantee in the case where the graph is a star. For integers n≥2n\geq 2 and k≥3k\geq 3, define

Let n≥2n\geq 2 and k≥3k\geq 3, and let GG be a star with kk edges. There exists a connected allocation with egalitarian welfare at least f(n,k)f(n,k). Moreover, the bound f(n,k)f(n,k) is tight.

The values of f(n,k)f(n,k) for small nn and kk are shown in Table 1.

We proceed by induction on nn. For the base case n=2n=2, the lower bound of 1/31/3 follows from Theorem 3.1. To see that 1/31/3 is also an upper bound, assume that both agents value three of the edges uniformly at exactly 1/31/3 and have no value for the remaining k−3k-3 edges. Any connected allocation with egalitarian welfare greater than 1/31/3 would give rise to a connected allocation of a three-edge star with egalitarian welfare greater than 1/31/3, which by Theorem 3.1 does not exist.

Assume that the statement holds for n−1n-1 agents. First, we show that there exists a connected allocation with egalitarian welfare at least f(n,k)f(n,k). If k≥2n−1k\geq 2n-1, this follows immediately from Theorem 3.1. Suppose that k≤2n−2k\leq 2n-2. We have n+⌈k/2⌉−1≥n+k/2−1≥k+22+k2−1=kn+\lceil k/2\rceil-1\geq n+k/2-1\geq\frac{k+2}{2}+\frac{k}{2}-1=k, or f(n,k)≤1/kf(n,k)\leq 1/k. Hence, every agent has value at least f(n,k)f(n,k) for some edge of the star. We choose one such edge for an arbitrary agent and move a knife from its outer endpoint to the center of the star, stopping when the covered part has value f(n,k)f(n,k) for some agent ii. We allocate this piece of cake to agent ii, and make the cut point a new vertex in the remaining graph, which has value at least 1−f(n,k)1-f(n,k) for each of the remaining agents. The remaining graph is still a star with kk edges (possibly with a degenerate edge), so by the inductive hypothesis, there exists a connected allocation of the remaining graph to the n−1n-1 agents with egalitarian welfare at least

where the first equality follows from the observation that f(n−1,k)=1n+⌈k/2⌉−2f(n-1,k)=\frac{1}{n+\lceil k/2\rceil-2} for all k≤2n−2k\leq 2n-2.

Next, we show that f(n,k)f(n,k) is tight for all nn and kk. If k≥2n−1k\geq 2n-1, this follows from the instance in Theorem 3.1 and by adding extra edges of zero value. Suppose that k≤2n−2k\leq 2n-2 and that the agents have identical valuations. Each agent has value f(n,k)f(n,k) for k−1k-1 of the edges and 1−(k−1)⋅f(n,k)1-(k-1)\cdot f(n,k) for the kkth edge, and the values are distributed uniformly across each edge. Note that as in the preceding paragraph, we have f(n,k)≤1/kf(n,k)\leq 1/k, and therefore 1−(k−1)⋅f(n,k)≥f(n,k)1-(k-1)\cdot f(n,k)\geq f(n,k). Assume for contradiction that there is a connected allocation with egalitarian welfare strictly greater than f(n,k)f(n,k). Any agent must either receive intervals from at least two edges (perhaps including the kkth edge), or only receive an interval from the kkth edge. The number of agents of the first type is at most ⌊k/2⌋\lfloor k/2\rfloor. The number of agents of the second type is strictly less than

This means that the total number of agents is strictly less than ⌊k/2⌋+(n−⌊k/2⌋)=n\lfloor k/2\rfloor+(n-\lfloor k/2\rfloor)=n, yielding the desired contradiction. ∎

Two Agents

In this section, we focus on the case of two agents. We establish the optimal egalitarian welfare that can be obtained for each graph and derive utility frontiers when the agents may have different entitlements. In addition, we explore the extent to which our guarantees can be improved if we allow more than one connected piece per agent, and also consider approximate equitability.

Before we can state our results for specific graphs, we need some graph-theoretic terminology. Recall that a bridge of a graph is an edge that is not contained in any cycle. A graph is said to be bridgeless if it contains no bridges.

A graph is said to be almost bridgeless if we can add an edge so that the resulting graph is bridgeless.

Note that according to this definition, every connected bridgeless graph with at least two vertices is also almost bridgeless, since we can add a copy of an existing edge.

Next, we define an oriented labeling of a graph.

An oriented labeling of a graph with mm edges is a labeling of the edges with numbers 1,2,…,m1,2,\dots,m, using each number exactly once, together with a labeling of one endpoint of each edge ii with i−i^{-} and the other endpoint with i+i^{+} (so each vertex receives a number of labels equal to the number of edges adjacent to it). An oriented labeling is said to be contiguous if:

For each 2≤i≤m2\leq i\leq m, the edges labeled 1,2,…,i−11,2,\dots,i-1 form a connected subgraph, and the vertex labeled i−i^{-} belongs to one of these edges.

For each 1≤i≤m−11\leq i\leq m-1, the edges labeled i+1,i+2,…,mi+1,i+2,\dots,m form a connected subgraph, and the vertex labeled i+i^{+} belongs to one of these edges.

It turns out that a graph admitting a contiguous oriented labeling is equivalent to it being almost bridgeless.

A graph is almost bridgeless if and only if it admits a contiguous oriented labeling.

(⇐\Leftarrow) Assume that a graph admits a contiguous oriented labeling. Add an edge between the vertices labeled 1−1^{-} and m+m^{+}. We claim that the resulting graph is bridgeless. Since the vertices 1−1^{-} and m+m^{+} are connected in the original graph, the new edge is part of a cycle. Now, consider any edge in the original graph; assume that the edge has label ii. The vertices 1−1^{-} and i−i^{-} are connected by a path that only goes through edges between 11 and i−1i-1. Likewise, the vertices i+i^{+} and m+m^{+} are connected by a path that only goes through edges between i+1i+1 and mm. Hence, the edge ii belongs to a cycle that goes through the two paths, the edge between m+m^{+} and 1−1^{-}, and itself.

(⇒\Rightarrow) Assume that a graph is almost bridgeless. We will label all edges with labels 1,2,…,m1,2,\dots,m and orient each edge in one direction (the source of edge ii corresponds to the vertex i−i^{-} and the sink to the vertex i+i^{+}) so that the labeling is a contiguous oriented labeling.

Suppose that the graph becomes bridgeless if we add an edge uvuv. Consider a path from uu to vv, and sort the edges and orient them along this path. We will iteratively construct ears until all edges are used. Each ear is a path starting at a vertex of a previous ear and ending at a vertex of a previous ear (possibly the same as the former vertex, in which case the path becomes a cycle) but not going through any other vertex of a previous ear; the only exception is the first ear, which is the path from uu to vv. Suppose that we have constructed some ears, and not all edges have been used. If there are edges that connect only vertices in the existing ears, we make each such edge into a new ear. If some edges still remain after this process, then since the graph is connected, there must be an edge xyxy such that xx belongs to an existing ear but yy does not. By assumption, xyxy is contained in a cycle if the edge uvuv is added, so we can follow the edges in this cycle until we reach a vertex zz in an existing ear for the first time (possibly z=xz=x). Since we stop if we reach either uu or vv, edge uvuv cannot be part of this trail, so we have a new ear. Assume without loss of generality that either x=ux=u, or the first edge directed into xx appears no later than the first edge directed into zz in the current edge order, or both. Orient the edges of the new ear along the trail from xx to zz. If x=ux=u, insert these edges consecutively at the beginning of the order. Else, insert them consecutively after the first edge directed into xx. After all edges have been added, label them from 11 to mm according to the final order. Observe that the edge with label 11 is always adjacent to uu, and the edge with label mm is always adjacent to vv.

We claim that the resulting oriented labeling is contiguous. First, we show that for each 1≤i≤m1\leq i\leq m, the edges labeled 1,2,…,i1,2,\dots,i form a connected subgraph. We proceed by induction on ii, with the base case i=1i=1 holding trivially. Assume that the edges 1,2,…,i−11,2,\dots,i-1 form a connected subgraph for some i≥2i\geq 2. If edge ii is not the first edge in its ear, its predecessor in its ear has label at most i−1i-1, so the induction hypothesis implies that the edges 1,2,…,i1,2,\dots,i form a connected subgraph. Moreover, in this case, vertex i−i^{-} belongs to the predecessor edge with label at most i−1i-1. Suppose now that edge ii is the first edge in its ear, and assume that the edge is directed from xx to yy. If x=ux=u, then since i≥2i\geq 2, the edge with label 11 is an edge with a lower label that is adjacent to uu. Else, the first edge directed into xx has label at most i−1i-1. In either case, the induction hypothesis implies that the edges 1,2,…,i1,2,\dots,i form a connected subgraph, and vertex i−=xi^{-}=x is adjacent to a vertex with label at most i−1i-1. This completes the induction and moreover shows that for each 2≤i≤m2\leq i\leq m, vertex i−i^{-} belongs to one of the edges 1,2,…,i−11,2,\dots,i-1.

Next, we show that for each 1≤i≤m1\leq i\leq m, the edges labeled i,i+1,…,mi,i+1,\dots,m form a connected subgraph. We proceed by downward induction on ii, with the base case i=mi=m holding trivially. Assume that the edges i+1,i+2,…,mi+1,i+2,\dots,m form a connected subgraph for some i<mi<m. If edge ii is not the last edge in its ear, its successor in its ear has label at least i+1i+1, so the induction hypothesis implies that the edges i,i+1,…,mi,i+1,\dots,m form a connected subgraph. Moreover, in this case, vertex i+i^{+} belongs to the successor edge with label at least i+1i+1. Suppose now that edge ii is the last edge in its ear, and assume that the edge is directed from yy to zz. If z=vz=v, then since i<mi<m, the edge with label mm is an edge with a higher label that is adjacent to vv. Suppose that z≠vz\neq v, which also implies that ii does not belong to the first ear. Consider the moment when we insert the ear that contains ii, and assume that this ear begins at vertex xx. If x=ux=u, then the edges of this ear are placed at the beginning of the order; since zz appears in a previous ear, there is an edge adjacent to it that comes after edge yzyz in the order. Suppose therefore that x≠ux\neq u, so that at the moment before we insert the ear containing ii, the first edge into xx appears no later than the first edge directed into zz in the order. We place the edges of the new ear after the first edge into xx. If x≠zx\neq z, there is an edge adjacent to zz that comes after this ear in the order. Else, x=zx=z, and this vertex is different from uu and vv. Consider the earliest ear that contains zz, and note that in this ear, there is an edge into zz and another edge out of zz; let i1i_{1} and i2i_{2} be the label of the two edges respectively. The first edge into zz appears no later than i1i_{1}, so the ear containing ii appears before i2i_{2} in the ordering. Hence, there is an edge with label at least i+1i+1 adjacent to zz. This completes the induction. It also follows from our argument that for each 1≤i≤m−11\leq i\leq m-1, the vertex i+i^{+} belongs to one of the edges i+1,i+2,…,mi+1,i+2,\dots,m. Combined with the previous paragraph, we find that our oriented labeling is contiguous, as claimed. ∎

Given a graph GG with kk vertices, a bipolar numbering of GG is a labeling of the vertices with numbers 1,2,…,k1,2,\dots,k, with each number used exactly once, such that every vertex with label greater than 11 has a neighbor with a smaller label and each vertex with label smaller than kk has a neighbor with a larger label. Bilò et al. (Bilò et al., 2019) characterized the class of graphs that admit a bipolar numbering as the graphs with the property that if the vertices of the graph represent indivisible items of possibly different values to the two agents, there always exists a connected ‘envy-free up to one item’ allocation. We show that the class of graphs that admit a bipolar numbering forms a strict subclass of the almost bridgeless graphs (which, by Lemma 4.3, is equivalent to the class of graphs that admit a contiguous oriented labeling).

Any graph that admits a bipolar numbering is almost bridgeless, but the converse does not hold.

Assume that a graph admits a bipolar numbering with the vertices labeled 1,2,…,k1,2,\dots,k. This means that for any vertex ii, there exists a path from 11 to ii that only goes through vertices 1,2,…,i1,2,\dots,i, and a path from ii to kk that only goes through vertices i,i+1,…,ki,i+1,\dots,k. Add an edge between vertices 11 and kk. We will show that the resulting graph is bridgeless, i.e., every edge is contained in a cycle. This is clear for the new edge. For any edge in the original graph between vertices ii and jj with i<ji<j, we can construct a cycle containing it by following a path from jj to kk that only uses vertices j,j+1,…,kj,j+1,\dots,k, traversing the added edge from kk to 11, and following a path from 11 to ii that only uses vertices 1,2,…,i1,2,\dots,i.

To show that the converse does not hold, consider the graphs shown in Figure 1. Since every edge in both graphs is contained in a cycle, both graphs are bridgeless and therefore almost bridgeless. On the other hand, one can check that neither graph admits a bipolar numbering. ∎

We are now ready to show our classification result: the optimal egalitarian welfare that can always be obtained for a graph is 1/21/2 if the graph is almost bridgeless, and 1/31/3 otherwise. The former is shown in Theorem 4.5, while the latter follows from Theorems 3.1 and 4.7.

For n=2n=2 and any almost bridgeless graph GG, there exists a connected proportional allocation.

Suppose that GG is almost bridgeless. By Lemma 4.3, it admits a contiguous oriented labeling. We move a knife over the edges of GG in increasing order of the label. For each edge with label ii, the knife goes from vertex i−i^{-} to vertex i+i^{+}. If the knife is currently on edge ii, we stop when the piece of cake containing edges 1,2,…,i−11,2,\dots,i-1, together with the interval of edge ii between i−i^{-} and the current position of the knife, yields value exactly 1/21/2 to one of the agents. We allocate this piece of cake to the agent who receives value 1/21/2, and the remainder of the cake to the other agent. Both agents receive value at least 1/21/2 and, by definition of the labeling, obtain a connected allocation of the cake. ∎

Let FF be a nonempty set of bridges in a graph. If no path contains all bridges in FF, there exist three bridges in FF such that no path contains all three bridges.

Assume that no path contains all bridges in FF. Since bridges are not contained in cycles, there is a spanning tree TT that contains FF. Let T′T^{\prime} be a minimal subtree of TT that contains FF. Since T′T^{\prime} cannot be a path, it has a vertex vv with degree at least 33. Each of the (at least three) branches of vv must contain a bridge from FF—otherwise the branch can be removed to obtain a smaller subtree than T′T^{\prime}.

Let e1,e2,e3e_{1},e_{2},e_{3} be bridges contained in three distinct branches. Suppose for contradiction that they are contained in a path. By reversing the direction of the path if necessary, we may assume that the path traverses at least two of the edges away from vv with respect to T′T^{\prime}. Assume further that two of these edges are e1e_{1} and e2e_{2}, and that the path traverses e1e_{1} before e2e_{2}. After traversing e1e_{1}, the path must reach another vertex ww in T′T^{\prime} that lies on the same side as vv with respect to both e1e_{1} and e2e_{2} (possibly the endpoint of e1e_{1} or e2e_{2} closer to vv). By combining the portion of the path from e1e_{1} to ww with the path in T′T^{\prime} from ww to e1e_{1}, we find that e1e_{1} lies on a cycle, a contradiction. ∎

For n=2n=2 and any graph GG that is not almost bridgeless, there exist identical valuation functions of the two agents such that any connected allocation yields egalitarian welfare at most 1/31/3.

Suppose that GG is not almost bridgeless. Then no path can contain all bridges of GG: if there exists such a path, we can eliminate all bridges by adding an edge that connects the endpoints of this path. By Lemma 4.6, there exist three bridges of GG such that no path contains all three bridges. For each of the three bridges, the other two bridges must lie on the same side of it, since otherwise we can construct a path that contains all three bridges.

Assume that both agents value each of the three bridges exactly 1/31/3 (and every other edge ), and the value is distributed uniformly within each bridge. Suppose for contradiction that there exists a connected allocation with egalitarian welfare strictly greater than 1/31/3. This means that each agent must receive intervals from at least two bridges. However, when an agent receives intervals from two bridges, each interval must contain the endpoint of the bridge that is on the same side as the other two bridges. This is impossible since there are only three bridges, yielding the desired contradiction. ∎

2. Utility Frontiers

In this subsection, we establish the frontiers of the utilities that we can guarantee to the two agents regardless of the graph, assuming that the agents may have different entitlements. We begin by observing that the cut-and-choose protocol allows us to find an allocation that gives utility 1/21/2 to the first agent and 1/31/3 to the second agent; this generalizes the case n=2n=2 of Theorem 3.1.

For n=2n=2 and any graph GG, there exists a connected allocation such that the first agent receives value at least 1/21/2 and the second agent receives value at least 1/31/3.

By Theorem 3.1, there exists a partition of the cake into two connected pieces such that the second agent values both pieces at least 1/31/3. The first agent can then simply choose the piece that she prefers and obtain value at least 1/21/2. ∎

The next proposition follows from Theorem 3.1.

For n=2n=2, there exists a graph GG and identical valuations of the two agents such that any connected allocation yields egalitarian welfare at most 1/31/3.

To complete the utility frontier, we show that if we are required to give a utility of more than 1/21/2 to the first agent, it may be impossible to provide any nontrivial guarantee for the second agent.

Let α>1/2\alpha>1/2 and β>0\beta>0. There exists an instance with n=2n=2 such that no connected allocation yields value at least α\alpha to the first agent and at least β\beta to the second agent.

Fix α>1/2\alpha>1/2 and β>0\beta>0, and assume that GG consists of a single edge represented by the interval .Supposethatthefirstagentvaluestheentireinterval. Suppose that the first agent values the entire interval uniformly, while the second agent values the interval [1−α,α][1-\alpha,\alpha] uniformly and nothing else. In any connected allocation that yields value at least α\alpha to the first agent, this agent must receive the entire interval [1−α,α][1-\alpha,\alpha]. However, that means the second agent receives value from the allocation. ∎

Combining Theorem 4.8 with Propositions 4.9 and 4.10, we find that the values of (α,β)(\alpha,\beta) for which a connected allocation that yields utility α\alpha to the first agent and β\beta to the second agent always exists are as shown in Figure 2.

While Figure 1 completely captures the shares that can be guaranteed to the two agents, if we do not fix the entitlements of the agents in advance, it is possible to achieve better guarantees. As an example, consider the case where the graph GG consists of a single edge. In this case, Proposition 4.10 shows that any entitlements (α,β)(\alpha,\beta) with α>1/2\alpha>1/2 and β>0\beta>0 cannot be achieved. On the other hand, for any α∈\alpha\in, it is possible to give one agent a value of at least α\alpha and the other agent a value of at least 1−α1-\alpha (while not fixing which agent receives which share). Indeed, if we run a moving knife on the single edge and stop when the part already covered by the knife yields value α\alpha to some agent, the two pieces can be allocated to yield the desired guarantee. In what follows, we determine all shares (α,β)(\alpha,\beta) for which there always exists a connected allocation that yields value α\alpha to one agent and β\beta to the other agent regardless of the graph. Note that Theorem 4.8 carries over, and so does Proposition 4.9 since it holds for agents with identical valuations. We fill in the utility frontier, starting with the negative results.

Let α>1/2\alpha>1/2 and β>1/4\beta>1/4. There exists an instance with n=2n=2 and identical valuations such that no connected allocation yields value at least α\alpha to one agent and at least β\beta to the other agent.

Let GG be a star with four edges such that every agent values each edge exactly 1/41/4, and the value is distributed uniformly within the edge. Assume for contradiction that there is a connected allocation that yields value at least α\alpha to one agent and at least β\beta to the other agent; since the agents have identical valuations, we may assume without loss of generality that these are agents 1 and 2 respectively. Agent 1 must receive intervals from at least three edges, and these intervals must be connected via the center vertex. Note that the unallocated parts of these edges cannot be allocated to agent 2, since agent 2 would receive value less than 1/41/4. Similarly, agent 2 must receive intervals from at least two edges, and these intervals, which again must be connected via the center vertex, cannot be allocated to agent 1. However, this means that there must be at least five edges in total, a contradiction. ∎

Let α≤1/4\alpha\leq 1/4 and β>1−2α\beta>1-2\alpha. There exists an instance with n=2n=2 and identical valuations such that no connected allocation yields value at least α\alpha to one agent and at least β\beta to the other agent.

Choose ϵ>0\epsilon>0 such that β>1−2α+2ϵ\beta>1-2\alpha+2\epsilon. Let GG be the graph shown in Figure 3, where the value of each agent for each edge is as shown in the figure and distributed uniformly across the edge. Assume for contradiction that there is a connected allocation that yields value at least α\alpha to one agent and at least β\beta to the other agent; since the agents have identical valuations, we may assume without loss of generality that these are agents 1 and 2 respectively. Agent 2 must receive part of the middle edge; otherwise she has value at most 2(α−ϵ)<1/2<β2(\alpha-\epsilon)<1/2<\beta. Moreover, she must receive part of some left edge and part of some right edge; otherwise she has value at most 2(α−ϵ)+(1−4α+4ϵ)=1−2α+2ϵ<β2(\alpha-\epsilon)+(1-4\alpha+4\epsilon)=1-2\alpha+2\epsilon<\beta. Hence, the agent must receive the entire middle edge. This means that agent 1 can receive intervals from only one non-middle edge. Her value is therefore at most α−ϵ\alpha-\epsilon, a contradiction. ∎

We now move on to the positive result, which shows the additional guarantee that we can obtain if we give up control over which agent receives which entitlement.

Let α≤1/4\alpha\leq 1/4. For n=2n=2 and any graph GG, there exists a connected allocation such that one agent receives value at least α\alpha and the other agent receives value at least 1−2α1-2\alpha.

This follows immediately from Lemma 3.2 by taking HH to be the entire graph GG. ∎

Combining Theorem 4.13 with Propositions 4.11 and 4.12, we find that the values of (α,β)(\alpha,\beta) for which a connected allocation that yields utility α\alpha to one agent and β\beta to the other agent always exists are as shown in Figure 4.

3. Beyond One Connected Piece

As we mentioned in the introduction, one important motivation for considering connected allocations is to avoid situations where an agent receives a “union of crumbs”. In light of this motivation, it is interesting to explore whether we can obtain improved guarantees if we allow the agents to receive a small number of connected pieces. We demonstrate in this subsection that such improvements are indeed possible by presenting a tight bound of 12−12⋅3k\frac{1}{2}-\frac{1}{2\cdot 3^{k}} on the egalitarian welfare that can be guaranteed when a total of k+1k+1 connected pieces are permitted. We first establish the lower bound.

Let kk be a positive integer. For n=2n=2 and any graph GG, there exists an allocation in which the two agents receive a total of at most k+1k+1 connected pieces and the egalitarian welfare is at least 12−12⋅3k\frac{1}{2}-\frac{1}{2\cdot 3^{k}}.

Let GG be an arbitrary graph. It suffices to show that there exists a partition of GG into two parts with at most k+1k+1 connected pieces in total such that both parts yield value at least 12−12⋅3k\frac{1}{2}-\frac{1}{2\cdot 3^{k}} to the first agent. Indeed, given such a partition, we can let the second agent choose the part that she prefers and obtain value at least 1/21/2. We therefore consider only the first agent from now on.

We proceed by induction on kk; the base case k=1k=1 follows from Theorem 4.8. Suppose that the statement holds for k−1k-1, i.e., there exists a partition of GG into two parts with at most kk connected pieces in total such that both parts yield value at least 12−12⋅3k−1\frac{1}{2}-\frac{1}{2\cdot 3^{k-1}} to the agent. Assume without loss of generality that the second part has value at least 1/21/2, so the first part has value 12−x\frac{1}{2}-x for some 0≤x≤12⋅3k−10\leq x\leq\frac{1}{2\cdot 3^{k-1}}. Since the second part consists of at most k−1k-1 connected pieces, it contains a connected piece of value at least 12k−2\frac{1}{2k-2}. Denote this piece by HH.

Since 2k−2≤3k2k-2\leq 3^{k}, we have 2x3≤13k≤12k−2\frac{2x}{3}\leq\frac{1}{3^{k}}\leq\frac{1}{2k-2}. By creating a duplicate of our agent and applying Lemma 3.2, we can partition HH into two connected pieces in such a way that our agent has value in the range [2x3,4x3][\frac{2x}{3},\frac{4x}{3}] for the first piece. Move this piece from the second part of our partition of GG to the first part. The resulting partition of GG consists of at most k+1k+1 connected pieces in total, and the first part of this partition has value in the range [12−x3,12+x3][\frac{1}{2}-\frac{x}{3},\frac{1}{2}+\frac{x}{3}]. This implies that both parts of the partition yield value at least 12−x3≥12−12⋅3k\frac{1}{2}-\frac{x}{3}\geq\frac{1}{2}-\frac{1}{2\cdot 3^{k}}, completing the induction. ∎

Next, we show that the bound established in Theorem 4.14 is tight for every kk. First we need the following technical lemma.

Let tt be a positive integer, and let a1,a2,…,ata_{1},a_{2},\dots,a_{t} be (not necessarily distinct) integers and ε1,ε2,…,εt∈{±1,±2}\varepsilon_{1},\varepsilon_{2},\dots,\varepsilon_{t}\in\{\pm 1,\pm 2\}. Then

We proceed by strong induction on tt. The base case t=1t=1 follows from the observation that the terms of the form ε⋅3a\varepsilon\cdot 3^{a} closest to 1/21/2 are 1/31/3 and 2/32/3, and ∣1/3−1/2∣=∣2/3−1/2∣=1/6|1/3-1/2|=|2/3-1/2|=1/6. Suppose that the statement holds up to t−1t-1, and assume without loss of generality that a1≥a2≥⋯≥ata_{1}\geq a_{2}\geq\dots\geq a_{t}. We process the sum ε1⋅3a1+ε2⋅3a2+⋯+εt⋅3at\varepsilon_{1}\cdot 3^{a_{1}}+\varepsilon_{2}\cdot 3^{a_{2}}+\dots+\varepsilon_{t}\cdot 3^{a_{t}} from right to left. Consider the moment when we process terms involving 3a3^{a}. If there are two terms involving 3a3^{a} with coefficients of opposite signs, we either cancel them or combine them into one term. So we may assume that all terms with 3a3^{a} have the same sign, say positive. If there are two terms 1⋅3a1\cdot 3^{a}, we combine them into 2⋅3a2\cdot 3^{a}; if there is a term 1⋅3a1\cdot 3^{a} and 2⋅3a2\cdot 3^{a}, we combine them into 1⋅3a+11\cdot 3^{a+1}; and if there are two terms 2⋅3a2\cdot 3^{a}, we replace them with 1⋅3a1\cdot 3^{a} and 1⋅3a+11\cdot 3^{a+1}. Our operations do not increase the number of terms, so our procedure terminates with at most one term involving each power of 33.

If the number of terms ε⋅3a\varepsilon\cdot 3^{a} is now less than tt, we may apply the induction hypothesis and obtain our desired conclusion. Assume therefore that the number of terms is still tt, and a1>a2>⋯>ata_{1}>a_{2}>\dots>a_{t}. We have

If ε1\varepsilon_{1} is negative, we have ∑i=1tεi⋅3ai<−3a1+3a1=0\sum_{i=1}^{t}\varepsilon_{i}\cdot 3^{a_{i}}<-3^{a_{1}}+3^{a_{1}}=0, so the desired statement holds. Assume now that ε1\varepsilon_{1} is positive. If a1≤−2a_{1}\leq-2, we have ∑i=1tεi⋅3ai≤2⋅3a1+3a1=3a1+1≤1/3\sum_{i=1}^{t}\varepsilon_{i}\cdot 3^{a_{i}}\leq 2\cdot 3^{a_{1}}+3^{a_{1}}=3^{a_{1}+1}\leq 1/3, so the desired statement holds in this case.

Suppose that a1=−1a_{1}=-1. If ε1=1\varepsilon_{1}=1, we have

where the inequality follows from the inductive hypothesis. Similarly, if ε1=2\varepsilon_{1}=2, we have

Suppose now that a1=0a_{1}=0. If ε1=1\varepsilon_{1}=1, we have

where the first inequality follows from the inductive hypothesis. If ε1=2\varepsilon_{1}=2, we have ∑i=1tεi⋅3ai≥2−23−29−⋯=1\sum_{i=1}^{t}\varepsilon_{i}\cdot 3^{a_{i}}\geq 2-\frac{2}{3}-\frac{2}{9}-\dots=1, so the desired statement holds.

Finally, suppose that a1≥1a_{1}\geq 1. If ε1=2\varepsilon_{1}=2, we have ∑i=1tεi⋅3ai≥3ai(2−23−29−… )≥3\sum_{i=1}^{t}\varepsilon_{i}\cdot 3^{a_{i}}\geq 3^{a_{i}}\left(2-\frac{2}{3}-\frac{2}{9}-\dots\right)\geq 3, so the desired statement holds. Assume now that ε1=1\varepsilon_{1}=1. If a2=a1−1a_{2}=a_{1}-1 and ε2\varepsilon_{2} is negative, we may combine the terms 1⋅3a11\cdot 3^{a_{1}} and ε2⋅3a2\varepsilon_{2}\cdot 3^{a_{2}} into (3+ε2)⋅3a2(3+\varepsilon_{2})\cdot 3^{a_{2}} and apply the induction hypothesis. So we may assume that either a2≤a1−2a_{2}\leq a_{1}-2 or ε2\varepsilon_{2} is positive. In either case, we have ∑i=1tεi⋅3ai≥3a1(1−29−227−… )=3a1⋅23≥2\sum_{i=1}^{t}\varepsilon_{i}\cdot 3^{a_{i}}\geq 3^{a_{1}}\left(1-\frac{2}{9}-\frac{2}{27}-\dots\right)=3^{a_{1}}\cdot\frac{2}{3}\geq 2, so the desired statement again holds. ∎

Let kk be a positive integer. There exists an instance with n=2n=2 and identical valuations such that any allocation in which the two agents receive a total of at most k+1k+1 connected pieces yields egalitarian welfare at most 12−12⋅3k\frac{1}{2}-\frac{1}{2\cdot 3^{k}}.

Let GG be a rooted tree with k+2k+2 layers, where the first layer consists only of the root of the tree. The root has one child, and every vertex in subsequent layers up to the (k+1)(k+1)st layer has three children. In particular, the (k+2)(k+2)nd layer consists of 3k3^{k} leaves. The tree GG for the case k=2k=2 is shown in Figure 5. Suppose that both agents value each edge adjacent to a leaf exactly 1/3k1/3^{k} with the value distributed uniformly within the edge, and do not value any other edge.

Consider an arbitrary allocation in which the two agents receive a total of at most k+1k+1 connected pieces. We will show that the egalitarian welfare is at most 12−12⋅3k\frac{1}{2}-\frac{1}{2\cdot 3^{k}}. If there are unallocated parts of the cake, we arbitrarily allocate these parts so that the number of connected pieces that each agent receives does not increase; this does not lower the egalitarian welfare of the allocation. Hence we may assume that the entire cake is allocated (i.e., the allocation is complete). Denote by X1,…,XpX_{1},\dots,X_{p} the connected pieces that agent 1 receives, and Y1,…,YqY_{1},\dots,Y_{q} the connected pieces that agent 2 receives, where p+q≤k+1p+q\leq k+1. We assume that each edge has length 11, and refer to the distance along the (unique) path between two points in GG simply as the distance between these two points. Note that every connected piece has a unique point closest to the root: if there are two such points, they must be connected via a point that is strictly closer to the root than both of them. For every connected piece ZZ, denote by wzw_{z} the unique point in ZZ closest to the root and u(Z)u(Z) the utility of the piece ZZ. We will define a connected piece Z∗Z^{*} as follows:

If wzw_{z} is not a vertex of GG, let Z∗Z^{*} be the set of points ww such that the path from ww to the root goes through wzw_{z}. In other words, Z∗Z^{*} is the part of the tree “below” wzw_{z}.

If wzw_{z} is a vertex of GG, let Z∗Z^{*} be the set of points ww such that the intersection of ZZ and the path from ww to the root has nonzero measure. Equivalently, Z∗Z^{*} consists of the edges adjacent to wzw_{z} that have a nontrivial overlap with ZZ, along with everything “below” these edges.

Assume without loss of generality that agent 1 receives a piece containing the root of the tree. We claim that u(X1)+⋯+u(Xp)=[u(X1∗)+⋯+u(Xp∗)]−[u(Y1∗)+⋯+u(Yq∗)]u(X_{1})+\dots+u(X_{p})=[u(X_{1}^{*})+\dots+u(X_{p}^{*})]-[u(Y_{1}^{*})+\dots+u(Y_{q}^{*})]. First, note that for each Z∗Z^{*} where Z∈{X1,…,Xp,Y1,…,Yq}Z\in\{X_{1},\dots,X_{p},Y_{1},\dots,Y_{q}\}, every connected piece XiX_{i} and YiY_{i} is either contained in Z∗Z^{*} in its entirety or not at all. Hence u(Z∗)u(Z^{*}) can be written as a sum of distinct u(Xi)u(X_{i})’s and u(Yi)u(Y_{i})’s. Moreover, one can verify from the definition that a connected piece ZZ is contained in W∗W^{*} if and only if Z=WZ=W or the path from wzw_{z} to the root has a nontrivial overlap with WW. This path alternates between pieces XiX_{i} and YiY_{i} and ends with a piece XiX_{i}. Therefore, each u(Xi)u(X_{i}) is contained in u(X1∗)+⋯+u(Xp∗)u(X_{1}^{*})+\dots+u(X_{p}^{*}) exactly once more than in u(Y1∗)+⋯+u(Yq∗)u(Y_{1}^{*})+\dots+u(Y_{q}^{*}), while each u(Yi)u(Y_{i}) is contained in the two sums an equal number of times. This yields the claimed equality.

Next, observe that each u(Z∗)u(Z^{*}) can be written as 3s/3k3^{s}/3^{k} for some nonnegative integer s≤ks\leq k, or 2⋅3s/3k2\cdot 3^{s}/3^{k} for some nonnegative integer s≤k−1s\leq k-1, or δ/3k\delta/3^{k} for some δ∈\delta\in. Note also that since agent 11 receives a piece containing the root of the tree, for this piece XiX_{i} we have u(Xi∗)=1u(X_{i}^{*})=1. It follows that [u(X1∗)+⋯+u(Xp∗)]−[u(Y1∗)+⋯+u(Yq∗)][u(X_{1}^{*})+\dots+u(X_{p}^{*})]-[u(Y_{1}^{*})+\dots+u(Y_{q}^{*})] can be written as 1−(S+Δ)1-(S+\Delta), where SS is a sum of a number of terms (say, rr terms, where r≤kr\leq k) of the form ε⋅3a\varepsilon\cdot 3^{a} with ε∈{±1,±2}\varepsilon\in\{\pm 1,\pm 2\} and aa an integer, and ∣Δ∣≤(k−r)/3k|\Delta|\leq(k-r)/3^{k}. Hence, letting d:=∣u(X1)+⋯+u(Xp)−12∣d:=\left|u(X_{1})+\dots+u(X_{p})-\frac{1}{2}\right|, we have

where the first inequality follows from the triangle inequality, the second inequality follows from Lemma 4.15, and the last inequality holds since 3b≥2b+13^{b}\geq 2b+1 for any integer b≥0b\geq 0. This implies that the egalitarian welfare is at most 12−12⋅3k\frac{1}{2}-\frac{1}{2\cdot 3^{k}}, as claimed. ∎

Recall that the height of a rooted tree is the length of the longest path from the root to a leaf vertex. For example, a star rooted at the center vertex has height 11. Our next theorem shows that for graphs that can be represented as a tree of height at most 22, we can obtain full proportionality provided that we allow two connected pieces per agent.

For n=2n=2 and any graph GG that can be represented as a rooted tree of height at most 22, there exists a proportional allocation such that each agent receives at most two connected pieces.

Let GG be a rooted tree with root uu, and let v1,…,vkv_{1},\dots,v_{k} be the children of uu (see Figure 6). We move the knife in the following order: For i=1,2,…,ki=1,2,\dots,k, we move the knife from viv_{i} down to its first child, from viv_{i} down to its second child, and so on until we reach its last child, then from viv_{i} up to uu. This process ensures that the knife goes through all edges of GG. We stop when the part already covered by the knife is worth 1/21/2 to one of the agents. We allocate the covered part of the cake to that agent, and the remaining part to the other agent.

Clearly, the resulting allocation is proportional; it remains to show that each agent receives at most two connected pieces. We consider two cases:

Case 1: The knife stops on its way from a vertex viv_{i} to its child ww (possibly at ww). This means that the first i−1i-1 branches of the tree have been covered, and they are connected through uu. Moreover, the covered part in the iith branch are connected through viv_{i}. Hence the covered part forms two connected pieces of the cake. The uncovered part in the iith branch besides the edge viwv_{i}w is connected through viv_{i}, and it is connected to the remaining uncovered part from the (i+1)(i+1)st branch onwards through uu. The uncovered part of the edge viwv_{i}w forms one connected piece. It follows that both agents receive at most two connected pieces.

Case 2: The knife stops on its way from a vertex viv_{i} to the root uu (possibly at uu). The same argument as in Case 1 shows that the covered part forms two connected pieces of the cake. The uncovered part in the iith branch is contained in the edge viuv_{i}u, and it is connected to the remaining uncovered part from the (i+1)(i+1)st branch onwards through uu. It follows that both agents receive at most two connected pieces.

The two cases together complete the proof. ∎

4. Equitability

We end this section by briefly considering another well-established fairness notion: equitability. Interestingly, while for approximate proportionality it is useful to consider the maximum among the agents’ values for the current piece (Theorem 3.1), for approximate equitability in the case of two agents, the appropriate quantity to consider is the sum of these values. Note that an empty allocation is always equitable but yields the lowest possible welfare of zero, so we are interested in complete allocations.

For n=2n=2 and any graph GG, there exists a complete and connected allocation with inequity at most 1/31/3. Moreover, the bound 1/31/3 is tight.

To show tightness, let GG be a star with three edges such that every agent values each edge exactly 1/31/3, and the value is distributed uniformly within the edge. In any complete and connected allocation, one of the agents must receive two full edges (and possibly part of the third). This implies that the inequity in such an allocation is at least 1/31/3.

We now prove the first part of the theorem. Let GG be an arbitrary graph. Our goal is to find a complete, connected allocation (A1,A2)(A_{1},A_{2}) such that ∣f1(A1)−f2(A2)∣≤1/3|f_{1}(A_{1})-f_{2}(A_{2})|\leq 1/3. Since the allocation is complete, we may write f2(A2)=1−f2(A1)f_{2}(A_{2})=1-f_{2}(A_{1}). The desired condition can be rewritten as 2/3≤f1(A1)+f2(A1)≤4/32/3\leq f_{1}(A_{1})+f_{2}(A_{1})\leq 4/3. We use a similar procedure as in Theorem 3.1, turning the graph into a tree and considering a minimal subtree that has value at least 2/32/3 with respect to f1+f2f_{1}+f_{2}. We stop either when the knife cuts a subtree A1A_{1} such that f1(A1)+f2(A1)=2/3f_{1}(A_{1})+f_{2}(A_{1})=2/3 (Case 1), or when a set of branches A1A_{1} satisfies f1(A1)+f2(A1)≥2/3f_{1}(A_{1})+f_{2}(A_{1})\geq 2/3 for the first time (Case 2). An analogous argument shows that we must have f1(A1)+f2(A1)≤2/3+2/3=4/3f_{1}(A_{1})+f_{2}(A_{1})\leq 2/3+2/3=4/3, which yields the desired inequality. ∎

Chore Division

In this section, we assume that the graph represents a chore, i.e., an item that yields negative value to the agents. This models, for example, a situation where we wish to divide the responsibilities of maintaining a road or cable network.

For the case of two agents, all results in cake cutting (Section 4) can be translated to analogous results in chore division using a simple reduction. The idea is that given a chore instance, we can turn it into a cake instance by pretending that the cost functions are cake valuation functions, applying a result in the cake setting to obtain an initial allocation of the chore, and having the agents swap their assigned piece to arrive at the final allocation. This reduction works for translating positive results to the chore setting. For negative results, we can use the reduction in the opposite direction, starting from a chore instance and reducing it to a cake instance. As an illustrating example, we show how to deduce an analogue of Theorem 4.8 in the chore setting.

In chore division, for n=2n=2 and any graph GG, there exists a connected allocation such that the first agent incurs cost at most 1/21/2 and the second agent incurs cost at most 2/32/3.

Consider an arbitrary chore division instance. If we treat the chore valuations as cake valuations, then by Theorem 4.8, there exists a (complete) connected allocation such that the first agent receives value at least 1/21/2 and the second agent receives value at least 1/31/3. Let the agents swap their assigned pieces in this allocation. In the resulting allocation, which is also connected, the first agent incurs cost at most 1−1/2=1/21-1/2=1/2 and the second agent incurs cost at most 1−1/3=2/31-1/3=2/3. ∎

When there are more than two agents, the relationship between the cake and the chore setting becomes much less clear, and we do not know how to translate results from one setting to the other. In the chore setting, we show that for each nn, the egalitarian cost may need to be as high as 2n+1\frac{2}{n+1}.

In chore division, there exists a graph GG and identical valuations of the agents such that any connected allocation yields egalitarian cost at least 2n+1\frac{2}{n+1}.

Let GG be a star with n+1n+1 edges such that every agent has cost exactly 1n+1\frac{1}{n+1} for each edge, and the cost is distributed uniformly within the edge. Assume for contradiction that there is a connected allocation with egalitarian cost strictly less than 2n+1\frac{2}{n+1}. Let v1,…,vn+1v_{1},\dots,v_{n+1} be the endpoints of the edges different from the center of the star. For each ii, some agent must be allocated a piece containing viv_{i}. If an agent receives a piece containing two endpoints, she incurs cost at least 2n+1\frac{2}{n+1}, which is impossible. So every agent’s piece contains at most one endpoint viv_{i}. However, since there are nn agents and n+1n+1 endpoints, some endpoint is left unallocated, a contradiction. ∎

The bound 2n+1\frac{2}{n+1} is tight for n=2n=2 due to Theorem 5.1. Next, we show that it remains tight as long as n≤5n\leq 5. A simpler protocol for the case n=3n=3 is given in Appendix A.

In chore division, for n≤5n\leq 5 and any graph GG, there exists a connected allocation with egalitarian cost at most 2n+1\frac{2}{n+1}.

We proceed by strong induction on nn; the case n=1n=1 is trivial while the case n=2n=2 follows from Theorem 5.1. Let 3≤n≤53\leq n\leq 5. For an arbitrary piece of chore, let c1≤c2≤⋯≤cnc_{1}\leq c_{2}\leq\dots\leq c_{n} be the costs of the agents for the piece in increasing order. We define two conditions that the piece may satisfy:

Condition 1: c1≤1n+1c_{1}\leq\frac{1}{n+1}, and ci≤i−1n+1c_{i}\leq\frac{i-1}{n+1} for i=2,3,…,ni=2,3,\dots,n.

Condition 2: ci>i+1n+1c_{i}>\frac{i+1}{n+1} for i=1,2,…,n−1i=1,2,\dots,n-1, and cn>nn+1c_{n}>\frac{n}{n+1}.

We turn the graph GG into a tree as in Theorem 3.1. Choose an arbitrary vertex uu of the tree GG as its root. Let vv be a vertex such that the subtree rooted at vv does not satisfy Condition 1, but the subtree rooted at any child of vv does. Let w1,…,wkw_{1},\dots,w_{k} be the children of vv. We consider two cases:

Case 1: At least one of the kk branches of vv along with the corresponding subtree does not satisfy Condition 1. Assume without loss of generality that the branch containing w1w_{1} is one such branch. By our assumption, the subtree rooted at w1w_{1} satisfies Condition 1. Hence, by moving a knife from w1w_{1} to vv, we can find the point xx such that if we consider the interval [w1,x][w_{1},x] together with the subtree rooted at w1w_{1} as a subtree rooted at xx, at least one of the inequalities in Condition 1 is tight for this subtree and the remaining inequalities still hold. Assume that for each j=1,2,…,nj=1,2,\dots,n, agent jj has cost cjc_{j} for this subtree.

Suppose that the inequality involving cic_{i} is tight. If i=1i=1, we allocate this subtree to agent 1, who incurs cost 1n+1\frac{1}{n+1}. The rest of the chore has cost at most nn+1\frac{n}{n+1} to the remaining agents, and by the inductive hypothesis, it can be allocated in a connected manner to these agents so that each agent incurs cost at most 2n⋅nn+1=2n+1\frac{2}{n}\cdot\frac{n}{n+1}=\frac{2}{n+1}. Suppose now that i≥2i\geq 2. This means that ci=i−1n+1c_{i}=\frac{i-1}{n+1}. The subtree has cost at most i−1n+1\frac{i-1}{n+1} to the first i−1i-1 agents. By the inductive hypothesis, it can be allocated in a connected manner to these agents so that each agent incurs cost at most 2i⋅i−1n+1<2n+1\frac{2}{i}\cdot\frac{i-1}{n+1}<\frac{2}{n+1}. The rest of the chore has cost at most n−i+2n+1\frac{n-i+2}{n+1} to the remaining n−i+1n-i+1 agents. By the inductive hypothesis, it can be allocated in a connected manner to these agents so that each agent incurs cost at most 2n−i+2⋅n−i+2n+1=2n+1\frac{2}{n-i+2}\cdot\frac{n-i+2}{n+1}=\frac{2}{n+1}. Hence we have a connected allocation with egalitarian cost at most 2n+1\frac{2}{n+1}.

Case 2: Every branch of vv along with the corresponding subtree satisfies Condition 1. Let t∈{1,2,…,k}t\in\{1,2,\dots,k\} be the smallest number such that the first tt branches and their subtrees together, which we denote by TT, do not satisfy Condition 1. In particular, the first t−1t-1 branches and their subtrees together, which we denote by T1T_{1}, satisfy Condition 1, and the ttth branch and its subtree together, which we denote by T2T_{2}, also satisfy this condition.

We claim that TT does not satisfy Condition 2. Assume for contradiction that the opposite is true. Let a1≤⋯≤ana_{1}\leq\dots\leq a_{n} be the costs of the agents for T1T_{1} in increasing order, and b1≤⋯≤bnb_{1}\leq\dots\leq b_{n} be the corresponding costs for T2T_{2}. By Condition 1, we have a1≤1n+1a_{1}\leq\frac{1}{n+1} and ai≤i−1n+1a_{i}\leq\frac{i-1}{n+1} for i≥2i\geq 2; analogous upper bounds hold for the bib_{i}’s. In order for a sum ai+bja_{i}+b_{j} to be strictly greater than rn+1\frac{r}{n+1} for some positive integer rr, the upper bounds of aia_{i} and bjb_{j} must add up to at least r+1n+1\frac{r+1}{n+1}. Hence, in order for Condition 2 to be satisfied, we must have

Multiplying both sides by n+1n+1, this is equivalent to

or (n−1)(n−6)≥0(n-1)(n-6)\geq 0, which is false for 4≤n≤54\leq n\leq 5. So TT does not satisfy Condition 2.

Recall that TT does not satisfy Condition 1. Let c1≤⋯≤cnc_{1}\leq\dots\leq c_{n} be the costs of the agents for TT in increasing order, and let ii be the smallest index for which the inequality involving cic_{i} in Condition 1 fails. If i≥2i\geq 2, we may proceed as in Case 1 by allocating TT to the first i−1i-1 agents and the rest of the chore to the remaining n−i+1n-i+1 agents. So we may assume that i=1i=1, i.e., c1≥1n+1c_{1}\geq\frac{1}{n+1}. Next, let jj be the smallest index for which the inequality involving cjc_{j} in Condition 2 fails. Since cn≥cn−1c_{n}\geq c_{n-1}, we have j<nj<n. This means that cr>r+1n+1c_{r}>\frac{r+1}{n+1} for r=1,2,…,j−1r=1,2,\dots,j-1 and cj≤j+1n+1c_{j}\leq\frac{j+1}{n+1}. Hence, TT has cost at most j+1n+1\frac{j+1}{n+1} to the first jj agents. By the inductive hypothesis, it can be allocated in a connected manner to these agents so that each agent incurs cost at most 2j+1⋅j+1n+1=2n+1\frac{2}{j+1}\cdot\frac{j+1}{n+1}=\frac{2}{n+1}. If j≥2j\geq 2, then since cj−1>jn+1c_{j-1}>\frac{j}{n+1}, the rest of the chore has cost at most n−j+1n+1\frac{n-j+1}{n+1} to the remaining n−jn-j agents. If j=1j=1, we know that c1≥1n+1c_{1}\geq\frac{1}{n+1}, and so the rest of the chore has cost at most nn+1=n−j+1n+1\frac{n}{n+1}=\frac{n-j+1}{n+1} to the remaining n−1n-1 agents. In either case, by the inductive hypothesis, the rest of the chore can be allocated in a connected manner to these agents so that each agent incurs cost at most 2n−j+1⋅n−j+1n+1=2n+1\frac{2}{n-j+1}\cdot\frac{n-j+1}{n+1}=\frac{2}{n+1}. Hence we again have a connected allocation with egalitarian cost at most 2n+1\frac{2}{n+1}.

The two cases together complete the proof. ∎

We conjecture that the bound 2n+1\frac{2}{n+1} is tight for all nn, and leave it as an intriguing open question.

Conclusion and Future Work

In this paper, we introduce and study a generalized version of the classical cake-cutting problem, where the cake can be represented by an arbitrary graph instead of an interval. We establish bounds on the utilities that can be guaranteed to the agents for various classes of graphs, both for cake cutting and chore division, and demonstrate in several cases that our guarantees are tight. We also show that better guarantees are possible if we allow more connected pieces per agent, and exhibit an algorithm that computes an approximately equitable allocation.

Our work opens up a number of new directions for future research. Besides proportionality and equitability, another prominent fairness notion is envy-freeness, which stipulates that no agent prefers another agent’s bundle to her own in the allocation. In the case of two agents, envy-freeness and proportionality are equivalent, and approximate proportionality bounds readily translate to corresponding approximate envy-freeness results. However, this equivalence ceases to hold when there are more than two agents. If the graph consists of a single edge, a connected envy-free allocation always exists for any number of agents (Stromquist, 1980). It would be interesting to see whether one can obtain (approximate) envy-freeness guarantees for different classes of graphs.

Like in the vast majority of the fair division literature, we assume in this paper that all parts of the resource either yield nonnegative utility to every agent (cake cutting) or nonpositive utility to every agent (chore division). Recently, Bogomolnaia et al. (Bogomolnaia et al., 2017) and Segal-Halevi (Segal-Halevi, 2018) considered a generalization where an agent may have positive utility for some parts of the resource and negative utility for other parts, and different agents may have different evaluations. Aziz et al. (Aziz et al., 2019) showed the existence of a connected proportional allocation in this general setting when the resource is represented by an interval. Again, extending this result to more complex graphs is an appealing direction that we leave for future work.

References

Appendix A Chore Division Protocol for Three Agents

In chore division, for n=3n=3 and any graph GG, there exists a connected allocation with egalitarian cost at most 1/21/2.

Pick two arbitrary agents. By Theorem 5.1, there exists a connected allocation to the two agents such that the first agent incurs cost at most 1/21/2 and the second agent incurs cost at most 2/32/3. Fix the piece assigned to the first agent, and divide the piece assigned to the second agent further between the second and third agents. By Theorem 5.1 again, there exists a connected allocation of the latter piece such that the third agent incurs cost at most 1/21/2 and the second agent incurs cost at most 2/3×2/3=4/9<1/22/3\times 2/3=4/9<1/2. Hence the egalitarian cost of the resulting allocation is at most 1/21/2. ∎