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Event-driven dynamic job shop scheduling execution based on improved Genetic Algorithm and Ontology
Xue LL(薛玲玲); Wang P(王鹏); Cheng HB(程海波); Zeng P(曾鹏); Yu HB(于海斌)
作者部门工业控制网络与系统研究室
会议名称2017 Chinese Automation Congress (CAC2017) & China Intelligent Manufacturing International Conference (CIMIC2017)
会议日期October 20-22, 2017
会议地点Jinan, China
会议录名称2017 Chinese Automation Congress (CAC2017) & China Intelligent Manufacturing International Conference (CIMIC2017)
出版者IEEE
出版地New York
2017
页码6430-6435
收录类别EI ; CPCI(ISTP)
EI收录号20183005610140
WOS记录号WOS:000427816106093
产权排序1
ISBN号978-1-5386-3524-7
关键词Dynamic Job Shop Scheduling Problems Improved Genetic Algorithm Ontology Module
摘要

This paper proposes an improved Genetic Algorithm (IGA}-combined with ontology module to sol\'c dynamic job shop scheduling problem (DJSSP). The objective function of this scheduling problem is to minimize a weighted sum method of maximum complete time (makespan) and mean waiting time to periodically plan production. This scheduling method is applied to a flexible manufacturing system. A reschedule strategy is utilized to solve dynamic disturbances happened during manufacturing process. Experimental results show that schedule can be repaired efficiently and correctly without obviously affecting the scheduling.

语种英语
引用统计
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/21327
专题工业控制网络与系统研究室
通讯作者Xue LL(薛玲玲)
作者单位1.Lab. of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.University of Chinese Academy of Sciences, Beijing 100049, China
推荐引用方式
GB/T 7714
Xue LL,Wang P,Cheng HB,et al. Event-driven dynamic job shop scheduling execution based on improved Genetic Algorithm and Ontology[C]. New York:IEEE,2017:6430-6435.
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