In the fair cake-cutting problem, the partners often have different entitlements. For example, the resource may belong to two shareholders such that Alice holds 8/13 and George holds 5/13. This leads to the criterion of weighted proportionality (WPR): there are several weights that sum up to 1, and every partner should receive at least a fraction of the resource by their own valuation.
In contrast, in the simpler proportional cake-cutting setting, the weights are equal: for all
Several algorithms can be used to find a WPR division.
Suppose all the weights are rational numbers, with common denominator . So the weights are , with . For each player , create clones with the same value-measure. The total number of clones is . Find a proportional cake allocation among them. Finally, give each partner the pieces of his clones.
Robertson and Webb [1] : 36 show a simpler procedure for two partners: Alice cuts the cake into pieces equal in her eyes; George selects the most valuable pieces in his eyes, and Alice takes the remaining pieces.
This simple procedure requires cuts, which may be very large. For example, if Alice is entitled to 8/13 and George is entitled to 5/13, then 13-1=12 cuts are needed in the initial partition.
The number of required queries is
Suppose a cake has to be divided among Alice and George, Alice is entitled to 8/13 and George is entitled to 5/13. The cake can be divided as follows.
Now there are two "good" cases - cases in which we can use these pieces to attain a weighted-proportional division respecting the different entitlements:
Case 1: There is a subset of the marked pieces whose sum is 5. E.g., if George marks the 3-piece and the three 1-pieces. Then, this subset is given to George and the remainder is given to Alice. George now has at least 5/13 and Alice has exactly 8/13.
Case 2: There is a subset of the unmarked pieces whose sum is 8. E.g., if George marks the 3-piece and only one 1-piece. Then, this subset is given to Alice and the remainder is given to George. Alice now has exactly 8 and George has given up a sum of less than 8, so he has at least 5/13.
It is possible to prove that the good cases are the only possible cases. I.e, every subset of 5:3:2:1:1:1, EITHER has a subset that sums to 5, OR its complement has a subset that sums to 8. Hence, the above algorithm always finds a WPR allocation with the given ratios. The number of cuts used is only 5.
McAvaney, Robertson and Webb [1] : 36–41 [2] generalize this idea using the concept of Ramsey partitions (named after the Ramsey theory).
Formally: if and are positive integers, a partition of is called a Ramsey partition for the pair , if for any sub-list , either there is a sublist of which sums to , or there is a sublist of which sums to .
In the example above, and and the partition is 5:3:2:1:1:1, which is a Ramsey partition. Moreover, this is the shortest Ramsey partition in this case, so it allows us to use a small number of cuts.
Ramsey partitions always exist. Moreover, there is always a unique shortest Ramsey partition. It can be found using a simple variant of the Euclidean algorithm. The algorithm is based on the following lemma: [1] : 143–144
This lemma leads to the following recursive algorithm.
:
Once a minimal Ramsey partition is found, it can be used to find a WPR division respecting the entitlements.
The algorithm needs at least cuts, where is the golden ratio. In most cases, this number is better than making cuts. But if , then cuts are needed, since the only Ramsey partition of the pair is a sequence with ones.
Suppose again that Alice is entitled to 8/13 and George is entitled to 5/13. The cake can be divided as follows.
The general idea is similar to the Even-Paz protocol: [1] : 42–44 :
The cut-near-halves algorithm needs at most cuts, so it is always more efficient than the Ramsey-partitions algorithm.
The cut-near-halves algorithm is not always optimal. For example, suppose the ratio is 7:3.
It is an open question how to find the best initial cut for each entitlement ratio.
The algorithm can be generalized to n agents; the number of required queries is
Cseh and Fleiner [3] presented an algorithm for dividing a multi-dimensional cake among any number of agents with any entitlements (including irrational entitlements), in a finite number of queries. Their algorithm requires queries in the Robertson–Webb query model; thus it is more efficient than agent-cloning and cut-near-halves. They prove that this runtime complexity is optimal.
When the entitlements are not rational numbers, methods based on cloning cannot be used since the denominator is infinite. Shishido and Zeng presented an algorithm called mark-cut-choose, that can also handle irrational entitlements, but with an unbounded number of cuts. [4]
The algorithm of Cseh and Fleiner can also be adapted to work with irrational entitlements in a finite number of queries. [5]
Besides the number of required queries, it is also interesting to minimize the number of required cuts, so that the division is not too much fractioned. The Shishido-Zeng algorithms yield a fair division with at most cuts, and a strongly-fair division with at most cuts. [4]
In the worst case, at least cuts might be required. Brams, Jones and Klamler [6] show an example for n=2. A cake made of four consecutive regions has to be divided between Alice and George, whose valuations are as follows:
Alice's value | 2 | 2 | 2 | 2 |
George's value | 1 | 3 | 3 | 1 |
Note that the total cake value is 8 for both partners. If , then Alice is entitled to a value of at least 6. To give Alice her due share in a connected piece, we must give her either the three leftmost slices or the three rightmost slices. In both cases George receives a piece with a value of only 1, which is less than his due share of 2. To achieve a WPR division in this case, we must give George his due share in the center of the cake, where his value is relatively large, but then Alice will get two disconnected pieces. [7]
Segal-Halevi [8] shows that, if the cake is circular (i.e. the two endpoints are identified) then a connected WPR division for two people is always possible; this follows from the Stromquist–Woodall theorem. By recursively applying this theorem to find exact divisions, it is possible to get a WPR division using at most cuts when n is a power of 2, and a similar number when n is general.
Crew, Narayanan and Spirkle [9] improved this upper bound to 3n-4 using the following protocol:
The exact number of required cuts remains an open question. The simplest open case is when there are 3 agents and the weights are 1/7, 2/7, 4/7. It is not known if the number of required cuts is 4 (as in the lower bound) or 5 (as in the upper bound).
Zeng [10] presented an algorithm for approximate envy-free cake-cutting with different entitlements.
The bin packing problem is an optimization problem, in which items of different sizes must be packed into a finite number of bins or containers, each of a fixed given capacity, in a way that minimizes the number of bins used. The problem has many applications, such as filling up containers, loading trucks with weight capacity constraints, creating file backups in media and technology mapping in FPGA semiconductor chip design.
In game theory, fair division is the problem of dividing a set of resources among several people who have an entitlement to them, such that each person receives their due share. This problem arises in various real-world settings, such as: division of inheritance, partnership dissolutions, divorce settlements, electronic frequency allocation, airport traffic management, and exploitation of Earth observation satellites. This is an active research area in mathematics, economics, dispute resolution, and more. The central tenet of fair division is that such a division should be performed by the players themselves, maybe using a mediator but certainly not an arbiter as only the players really know how they value the goods.
An envy-free cake-cutting is a kind of fair cake-cutting. It is a division of a heterogeneous resource ("cake") that satisfies the envy-free criterion, namely, that every partner feels that their allocated share is at least as good as any other share, according to their own subjective valuation.
The Austin moving-knife procedures are procedures for equitable division of a cake. They allocate each of n partners, a piece of the cake which this partner values as exactly of the cake. This is in contrast to proportional division procedures, which give each partner at least of the cake, but may give more to some of the partners.
Chore division is a fair division problem in which the divided resource is undesirable, so that each participant wants to get as little as possible. It is the mirror-image of the fair cake-cutting problem, in which the divided resource is desirable so that each participant wants to get as much as possible. Both problems have heterogeneous resources, meaning that the resources are nonuniform. In cake division, cakes can have edge, corner, and middle pieces along with different amounts of frosting. Whereas in chore division, there are different chore types and different amounts of time needed to finish each chore. Similarly, both problems assume that the resources are divisible. Chores can be infinitely divisible, because the finite set of chores can be partitioned by chore or by time. For example, a load of laundry could be partitioned by the number of articles of clothing and/or by the amount of time spent loading the machine. The problems differ, however, in the desirability of the resources. The chore division problem was introduced by Martin Gardner in 1978.
Exact division, also called consensus division, is a partition of a continuous resource ("cake") into some k pieces, such that each of n people with different tastes agree on the value of each of the pieces. For example, consider a cake which is half chocolate and half vanilla. Alice values only the chocolate and George values only the vanilla. The cake is divided into three pieces: one piece contains 20% of the chocolate and 20% of the vanilla, the second contains 50% of the chocolate and 50% of the vanilla, and the third contains the rest of the cake. This is an exact division, as both Alice and George value the three pieces as 20%, 50% and 30% respectively. Several common variants and special cases are known by different terms:
Fair cake-cutting is a kind of fair division problem. The problem involves a heterogeneous resource, such as a cake with different toppings, that is assumed to be divisible – it is possible to cut arbitrarily small pieces of it without destroying their value. The resource has to be divided among several partners who have different preferences over different parts of the cake, i.e., some people prefer the chocolate toppings, some prefer the cherries, some just want as large a piece as possible. The division should be unanimously fair - each person should receive a piece that he or she believes to be a fair share.
Edmonds–Pruhs protocol is a protocol for fair cake-cutting. Its goal is to create a partially proportional division of a heterogeneous resource among n people, such that each person receives a subset of the cake which that person values as at least 1/an of the total, where is some sufficiently large constant. It is a randomized algorithm whose running time is O(n) with probability close to 1. The protocol was developed by Jeff Edmonds and Kirk Pruhs, who later improved it in joint work with Jaisingh Solanki.
Efficient cake-cutting is a problem in economics and computer science. It involves a heterogeneous resource, such as a cake with different toppings or a land with different coverings, that is assumed to be divisible - it is possible to cut arbitrarily small pieces of it without destroying their value. The resource has to be divided among several partners who have different preferences over different parts of the cake, i.e., some people prefer the chocolate toppings, some prefer the cherries, some just want as large a piece as possible, etc. The allocation should be economically efficient. Several notions of efficiency have been studied:
Approximate max-flow min-cut theorems are mathematical propositions in network flow theory. They deal with the relationship between maximum flow rate ("max-flow") and minimum cut ("min-cut") in a multi-commodity flow problem. The theorems have enabled the development of approximation algorithms for use in graph partition and related problems.
The fair pie-cutting problem is a variation of the fair cake-cutting problem, in which the resource to be divided is circular.
Equitable (EQ) cake-cutting is a kind of a fair cake-cutting problem, in which the fairness criterion is equitability. It is a cake-allocation in which the subjective value of all partners is the same, i.e., each partner is equally happy with his/her share. Mathematically, that means that for all partners i and j:
A proportional cake-cutting is a kind of fair cake-cutting. It is a division of a heterogeneous resource ("cake") that satisfies the proportionality criterion, namely, that every partner feels that his allocated share is worth at least 1/n of the total.
Weller's theorem is a theorem in economics. It says that a heterogeneous resource ("cake") can be divided among n partners with different valuations in a way that is both Pareto-efficient (PE) and envy-free (EF). Thus, it is possible to divide a cake fairly without compromising on economic efficiency.
Utilitarian cake-cutting is a rule for dividing a heterogeneous resource, such as a cake or a land-estate, among several partners with different cardinal utility functions, such that the sum of the utilities of the partners is as large as possible. It is a special case of the utilitarian social choice rule. Utilitarian cake-cutting is often not "fair"; hence, utilitarianism is often in conflict with fair cake-cutting.
Symmetric fair cake-cutting is a variant of the fair cake-cutting problem, in which fairness is applied not only to the final outcome, but also to the assignment of roles in the division procedure.
Truthful cake-cutting is the study of algorithms for fair cake-cutting that are also truthful mechanisms, i.e., they incentivize the participants to reveal their true valuations to the various parts of the cake.
Maximin share (MMS) is a criterion of fair item allocation. Given a set of items with different values, the 1-out-of-n maximin-share is the maximum value that can be gained by partitioning the items into n parts and taking the part with the minimum value.
In computer science, the Robertson–Webb (RW) query model is a model of computation used by algorithms for the problem of fair cake-cutting. In this problem, there is a resource called a "cake", and several agents with different value measures on the cake. The goal is to divide the cake among the agents such that each agent will consider his/her piece as "fair" by his/her personal value measure. Since the agents' valuations can be very complex, they cannot - in general - be given as inputs to a fair division algorithm. The RW model specifies two kinds of queries that a fair division algorithm may ask the agents: Eval and Cut. Informally, an Eval query asks an agent to specify his/her value to a given piece of the cake, and a Cut query asks an agent to specify a piece of cake with a given value.