Parallel Genetic Algorithm for Job Shop Heterogeneous Multi-Objectives Scheduling Problem

被引：0
|
作者：
Wang, Changjun [1 ]
Jia, YongJi [1 ]
Wang, Bing [2 ]
机构：
[1] Donghua Univ, Sch Management, Shanghai, Peoples R China
[2] Shandong Univ, Sch Informat Engn, Weihai, Shandong, Peoples R China
来源：
2008 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS, VOLS 1-6 | 2008年
关键词：
Job shop scheduling; Game theory; Nash Equilibrium; Genetic algorithm;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Consider a special group of job shop scheduling problems, where both customers and manufacturer have independent and different objectives. It is specified as a two-layer optimization model based on Noncooperative Game. Nash Equilibrium (NE) schedule for heterogeneous customers is defined. A Parallel Genetic Algorithm (PGA) based solving method is designed. Each customer is assigned a subpopulation and evolves synchronously to achieve a set of competitive equilibrium, ie., NE schedule. The manufacturer chooses the best schedule according to its system objective to influence customer's strategic behaviors. Tests indicate that the proposed algorithm can well coordinate the requirements of the customers and manufacturer.
引用
收藏
页码：295 / +
页数：2
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