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Finding the nucleoli of large cooperative games

Finding the nucleoli of large cooperative games
Finding the nucleoli of large cooperative games
The nucleolus is one of the most important solution concepts in cooperative game theory as a result of its attractive properties - it always exists (if the imputation is non-empty), is unique, and is always in the core (if the core is non-empty). However, computing the nucleolus is very challenging because it involves the lexicographical minimization of an exponentially large number of excess values. We present a method for computing the nucleoli of large games, including some structured games with more than 50 players, using nested linear programs (LP). Although different variations of the nested LP formulation have been documented in the literature, they have not been used for large games because of the large size and number of LPs involved. In addition, subtle issues such as how to deal with multiple optimal solutions and with tight constraint sets need to be resolved in each LP in order to formulate and solve the subsequent ones. Unfortunately, this technical issue has been largely overlooked in the literature. We treat these issues rigorously and provide a new nested LP formulation that is smaller in terms of the number of large LPs and their sizes. We provide numerical tests for several games, including the general flow games, the coalitional skill games and the weighted voting games, with up to 100 players.
nucleolus, cooperative game, multi-level programming, payoff distribution, constraint generation, lexicographical minimization
0377-2217
1078-1092
Nguyen, Tri-Dung
a6aa7081-6bf7-488a-b72f-510328958a8e
Thomas, Lyn C.
a3ce3068-328b-4bce-889f-965b0b9d2362
Nguyen, Tri-Dung
a6aa7081-6bf7-488a-b72f-510328958a8e
Thomas, Lyn C.
a3ce3068-328b-4bce-889f-965b0b9d2362

Nguyen, Tri-Dung and Thomas, Lyn C. (2016) Finding the nucleoli of large cooperative games. European Journal of Operational Research, 248 (3), 1078-1092. (doi:10.1016/j.ejor.2015.08.017).

Record type: Article

Abstract

The nucleolus is one of the most important solution concepts in cooperative game theory as a result of its attractive properties - it always exists (if the imputation is non-empty), is unique, and is always in the core (if the core is non-empty). However, computing the nucleolus is very challenging because it involves the lexicographical minimization of an exponentially large number of excess values. We present a method for computing the nucleoli of large games, including some structured games with more than 50 players, using nested linear programs (LP). Although different variations of the nested LP formulation have been documented in the literature, they have not been used for large games because of the large size and number of LPs involved. In addition, subtle issues such as how to deal with multiple optimal solutions and with tight constraint sets need to be resolved in each LP in order to formulate and solve the subsequent ones. Unfortunately, this technical issue has been largely overlooked in the literature. We treat these issues rigorously and provide a new nested LP formulation that is smaller in terms of the number of large LPs and their sizes. We provide numerical tests for several games, including the general flow games, the coalitional skill games and the weighted voting games, with up to 100 players.

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Accepted/In Press date: 12 August 2015
e-pub ahead of print date: 29 August 2015
Published date: 1 February 2016
Keywords: nucleolus, cooperative game, multi-level programming, payoff distribution, constraint generation, lexicographical minimization
Organisations: Centre of Excellence for International Banking, Finance & Accounting, Operational Research

Identifiers

Local EPrints ID: 369724
URI: http://eprints.soton.ac.uk/id/eprint/369724
ISSN: 0377-2217
PURE UUID: 9f33b7bd-f454-47c7-af62-5450ae6149df
ORCID for Tri-Dung Nguyen: ORCID iD orcid.org/0000-0002-4158-9099

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Date deposited: 08 Oct 2014 14:47
Last modified: 15 Mar 2024 05:08

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Contributors

Author: Tri-Dung Nguyen ORCID iD
Author: Lyn C. Thomas

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