最小代价生成树对策SHAPLEY值的蒙特卡罗算法

Q4 Decision Sciences

Journal of the Operations Research Society of Japan Pub Date : 2020-01-31 DOI:10.15807/jorsj.63.31

Kazutoshi Ando, K. Takase

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引用次数: 3

摘要

在本文中，我们讨论了一种计算最小代价生成树对策的Shapley值的蒙特卡罗算法。我们为边际成本向量提供了更严格的上界和下界，并改进了先前研究中算法输出所需的排列数量的下界，以达到给定概率下的给定精度。此外，我们还提供了计算实验来估计蒙特卡罗算法所需的排列数的下界。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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MONTE CARLO ALGORITHM FOR CALCULATING THE SHAPLEY VALUES OF MINIMUM COST SPANNING TREE GAMES

In this paper, we address a Monte Carlo algorithm for calculating the Shapley values of minimum cost spanning tree games. We provide tighter upper and lower bounds for the marginal cost vector and improve a previous study’s lower bound on the number of permutations required for the output of the algorithm to achieve a given accuracy with a given probability. In addition, we present computational experiments for estimating the lower bound on the number of permutations required by the Monte Carlo algorithm.

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来源期刊

Journal of the Operations Research Society of Japan 管理科学-运筹学与管理科学

CiteScore

0.70

自引率

0.00%

发文量

审稿时长

12 months

期刊介绍： The journal publishes original work and quality reviews in the field of operations research and management science to OR practitioners and researchers in two substantive categories: operations research methods; applications and practices of operations research in industry, public sector, and all areas of science and engineering.