Fair Allocation Algorithms for Indivisible Items under Structured Conflict Constraints

TL;DR

This paper develops pseudo-polynomial algorithms and FPTAS for fair allocation of indivisible items with conflict constraints, extending previous results to new graph classes like convex bipartite graphs.

Contribution

It introduces algorithms for convex bipartite, bounded clique-width, and bounded tree-independence number conflict graphs, broadening the scope of tractable cases.

Findings

Algorithms for convex bipartite conflict graphs

Algorithms for graphs of bounded clique-width

Algorithms for graphs of bounded tree-independence number

Abstract

We consider the fair allocation of indivisible items to several agents with additional conflict constraints. These are represented by a conflict graph where each item corresponds to a vertex of the graph and edges in the graph represent incompatible pairs of items which should not be allocated to the same agent. This setting combines the issues of Partition and Independent Set and can be seen as a partial coloring of the conflict graph. In the resulting optimization problem each agent has its own valuation function for the profits of the items. We aim at maximizing the lowest total profit obtained by any of the agents. In a previous paper this problem was shown to be strongly \NP-hard for several well-known graph classes, e.g., bipartite graphs and their line graphs. On the other hand, it was shown that pseudo-polynomial time algorithms exist for the classes of chordal graphs, cocomparability graphs, biconvex bipartite graphs, and graphs of bounded treewidth. In this contribution we extend this line of research by developing pseudo-polynomial time algorithms that solve the problem for the class of convex bipartite conflict graphs, graphs of bounded clique-width, and graphs of bounded tree-independence number. The algorithms are based on dynamic programming and also permit fully polynomial-time approximation schemes (FPTAS).