文章基本信息

标题：Lot streaming based job-shop scheduling problem using hybrid genetic algorithm
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作者：Serdar Birogul ; Cetin Elmas ; Tuncay Yigit 等
期刊名称：Scientific Research and Essays
印刷版ISSN：1992-2248
出版年度：2011
卷号：6
期号：14
页码：2873-2887
DOI：10.5897/SRE10.152
语种：English
出版社：Academic Journals
摘要：Job shop scheduling problems (JSSP’s) are computationally complex problems. Lot streaming (LS) is the process of splitting a job into sublots to reduce its makespan on a sequence of machines. A lot can be split into a number of smaller lots in JSSP. However, planning decisions become more complex when lot streaming is allowed. Thus, the solution can be minimized both the idle time and total working time. In modern manufacturing environment, a factor that effects the scheduling is the size of lot streaming. In this paper, it is examined how the lot streaming affects both the Gantt scheme and the genetic algorithm, and how to adapt the Hybrid Genetic Algorithms (HGA) to JSSP. HGA has a new repair operator, together with crossover and mutation operators. Experiments are conducted to show the effectiveness of the proposed repair algorithm.
关键词：Job-shop scheduling problem; genetic algorithms; lot streaming