Algorithmic solutions for maximizing shareable costs

Rong Zou, Boyue Lin, Marc Uetz*, Matthias Walter

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

32 Downloads (Pure)

Abstract

This article addresses the linear optimization problem to maximize the total costs that can be shared among a group of agents, while maintaining stability in the sense of the core constraints of a cooperative transferable utility game, or TU game. When maximizing total shareable costs, the cost shares must satisfy all constraints that define the core of a TU game, except for being budget balanced. The article first gives a fairly complete picture of the computational complexity of this optimization problem, its relation to optimization over the core itself, and its equivalence to other, minimal core relaxations that have been proposed earlier. We then address minimum cost spanning tree (MST) games as an example for a class of cost sharing games with non-empty core. While submodular cost functions yield efficient algorithms to maximize shareable costs, MST games have cost functions that are subadditive, but generally not submodular. Nevertheless, it is well known that cost shares in the core of MST games can be found efficiently. In contrast, we show that the maximization of shareable costs is (Formula presented.) -hard for MST games and derive a 2-approximation algorithm. Our work opens several directions for future research.

Original languageEnglish
Pages (from-to)385-397
Number of pages13
JournalNetworks
Volume84
Issue number4
Early online date25 Jun 2024
DOIs
Publication statusPublished - Dec 2024

Keywords

  • UT-Hybrid-D
  • cost sharing
  • minimum spanning tree game
  • computational complexity

Fingerprint

Dive into the research topics of 'Algorithmic solutions for maximizing shareable costs'. Together they form a unique fingerprint.

Cite this