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Efficient computation of the Shapley value for large-scale linear production games

Le, Phuoc Hoang, Nguyen, Tri-Dung, Bektaş, Tolga (2020) Efficient computation of the Shapley value for large-scale linear production games. Annals of Operations Research, 287 (2). pp. 761-781. ISSN 0254-5330. E-ISSN 1572-9338. (doi:10.1007/s10479-018-3047-0) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:92913)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL:
http://dx.doi.org/10.1007/s10479-018-3047-0

Abstract

The linear production game is concerned with allocating the total payoff of an enterprise among the owners of the resources in a fair way. With cooperative game theory providing a mathematical framework for sharing the benefit of the cooperation, the Shapley value is one of the widely used solution concepts as a fair measurement in this area. Finding the exact Shapley value for linear production games is, however, challenging when the number of players exceeds 30. This paper describes the use of linear programming sensitivity analysis for a more efficient computation of the Shapley value. The paper also proposes a stratified sampling technique to estimate the Shapley value for large-scale linear production games. Computational results show the effectiveness of the proposed methods compared to others. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.

Item Type: Article
DOI/Identification number: 10.1007/s10479-018-3047-0
Uncontrolled keywords: Cooperative games, Fairness, Linear production game, Payoff allocation, Shapley value
Subjects: H Social Sciences
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Tri-Dung Nguyen
Date Deposited: 17 Mar 2022 15:17 UTC
Last Modified: 18 Mar 2022 11:24 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/92913 (The current URI for this page, for reference purposes)

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