Utilitarian cake-cutting


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 inspired by the utilitarian philosophy. Utilitarian cake-cutting is often not "fair"; hence, utilitarianism is in conflict with fair cake-cutting.

Example

Consider a cake with two parts: chocolate and vanilla, and two partners: Alice and George, with the following valuations:
PartnerChocolateVanilla
Alice91
George64

The utilitarian rule gives each part to the partner with the highest utility. In this case, the utilitarian rule gives the entire chocolate to Alice and the entire Vanilla to George. The maxsum is 13.
The utilitarian division is not fair: it is not proportional since George receives less than half the total cake value, and it is not envy-free since George envies Alice.

Notation

The cake is called. It is usually assumed to be either a finite 1-dimensional segment, a 2-dimensional polygon or a finite subset of the multidimensional Euclidean plane.
There are partners. Each partner has a personal value function which maps subsets of to numbers.
has to be divided to disjoint pieces, one piece per partner. The piece allocated to partner is called, and.
A division is called utilitarian or utilitarian-maximal or maxsum if it maximizes the following expression:
The concept is often generalized by assigning a different weight to each partner. A division is called weighted-utilitarian-maximal if it maximizes the following expression:
where the are given positive constants.

Maxsum and Pareto-efficiency

Every WUM division with positive weights is obviously Pareto-efficient. This is because, if a division Pareto-dominates a division, then the weighted sum-of-utilities in is strictly larger than in, so cannot be a WUM division.
What's more surprising is that every Pareto-efficient division is WUM for some selection of weights.

Characterization of the maxsum rule

suggests a characterization to the WUM rule. The characterization is based on the following properties of a division rule R:
The following is proved for partners that assign positive utility to every piece of cake with positive size:

Disconnected pieces

When the value functions are additive, maxsum divisions always exist. Intuitively, we can give each fraction of the cake to the partner that values it the most, as in the [|example above]. Similarly, WUM divisions can be found by giving each fraction of the cake to the partner for whom the ratio is largest.
This process is easy to carry out when cake is piecewise-homogeneous, i.e., the cake can be divided to a finite number of pieces such that the value-density of each piece is constant for all partners.
When the cake is not piecewise-homogeneous, the above algorithm does not work since there is an infinite number of different "pieces" to consider.
Maxsum divisions still exist. This is a corollary of the Dubins–Spanier compactness theorem and it can also be proved using the Radon–Nikodym set.
However, no finite algorithm can find a maxsum division. Proof: A finite algorithm has value-data only about a finite number of pieces. I.e. there is only a finite number of subsets of the cake, for which the algorithm knows the valuations of the partners. Suppose the algorithm has stopped after having value-data about subsets. Now, it may be the case that all partners answered all the queries as if they have the same value measure. In this case, the largest possible utilitarian value that the algorithm can achieve is 1. However, it is possible that deep inside one of the pieces, there is a subset which two partners value differently. In this case, there exists a super-proportional division, in which each partner receives a value of more than, so the sum of utilities is strictly more than 1. Hence, the division returned by the finite algorithm is not maxsum.

Connected pieces

When the cake is 1-dimensional and the pieces must be connected, the simple algorithm of assigning each piece to the agent that values it the most no longer works, even when the pieces are piecewise-constant. In this case, the problem of finding a UM division is NP-hard, and furthermore no FPTAS is possible unless P=NP.
There is an 8-factor approximation algorithm, and a fixed-parameter tractable algorithm which is exponential in the number of players.
For every set of positive weights, a WUM division exists and can be found in a similar way.

Maxsum and fairness

A maxsum division is not always fair; see the example above. Similarly, a fair division is not always maxsum.
One approach to this conflict is to bound the "price of fairness" - calculate upper and lower bounds on the amount of decrease in the sum of utilities, that is required for fairness. For more details, see price of fairness.
Another approach to combining efficiency and fairness is to find, among all possible fair divisions, a fair division with a highest sum-of-utilities:

Finding maxsum-fair allocations

The following algorithms can be used to find an envy-free cake-cutting with maximum sum-of-utilities, for a cake which is a 1-dimensional interval, when each person may receive disconnected pieces and the value functions are additive:
  1. For partners with piecewise-constant valuations: divide the cake into m totally-constant regions. Solve a linear program with nm variables: each pair has a variable that determines the fraction of the region given to the agent. For each region, there is a constraint saying that the sum of all fractions from this region is 1; for each pair, there is a constraint saying that the first agent does not envy the second one. Note that the allocation produced by this procedure might be highly fractioned.
  2. For partners with piecewise-linear valuations: for each point in the cake, calculate the ratio between the utilities:. Give partner 1 the points with and partner 2 the points with, where is a threshold calculated so that the division is envy-free. In general cannot be calculated because it might be irrational, but in practice, when the valuations are piecewise-linear, can be approximated by an "irrational search" approximation algorithm. For any, The algorithm find an allocation that is -EF, and attains a sum that is at least the maximum sum of an EF allocation. Its run-time is polynomial in the input and in.
  3. For partners with general valuations: additive approximation to envy and efficiency, based on the piecewise-constant-valuations algorithm.

    Properties of maxsum-fair allocations

study both envy-free and equitable cake divisions, and relate them to maxsum and Pareto-optimality. As explained above, maxsum allocations are always PO. However, when maxsum is constrained by fairness, this is not necessarily true. They prove the following: