A Game-theory Based Optimization Approach for Job Scheduling in Virtual Manufacturing Networks

被引：1
|
作者：
Nie L. [1 ]
Zhang G. [2 ]
Wang X. [1 ]
Bai Y. [1 ]
机构：
[1] School of Intelligent Manufacturing and Control Engineering, Shanghai Second Polytechnic University, Shanghai
[2] School of Management Science and Engineering, Zhengzhou Institute of Aeronautical Industry Management, Zhengzhou
来源：
Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2019年 / 30卷 / 12期
关键词：
Game-theory; Genetic algorithm; Job scheduling; Nash equilibrium; Network cooperative strategy;
D O I：
10.3969/j.issn.1004-132X.2019.12.017
中图分类号：
学科分类号：
摘要：
A non-cooperative game model was put forward herein for job scheduling problems in virtual manufacturing networks, which transferred the problems into a game. The concept of D-minimum Nash equilibrium was proposed based on the analysis of the existence of ideal Nash equilibrium in game scheduling model. A Nash equilibrium solving method was proposed based on genetic algorithm in order to search the D-minimum Nash equilibrium of the game. In the genetic algorithm, a chromosome coding and decoding scheme and fitness function were designed according to the characteristics of job scheduling problems in virtual manufacturing networks. Efficiency of the proposed approach was validated on several benchmark instances. © 2019, China Mechanical Engineering Magazine Office. All right reserved.
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页码：1492 / 1497
页数：5
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