Research on Job Shop Scheduling Method based on Genetic Algorithm under Uncertainty

被引：0

作者：

Gao, Ya ^{[1
]}

Peng, Yunfang ^{[1
]}

机构：

[1] Shanghai Univ, Sch Management, Shanghai 200444, Peoples R China

来源：

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON LOGISTICS, ENGINEERING, MANAGEMENT AND COMPUTER SCIENCE (LEMCS 2015) | 2015年 / 117卷

关键词：

Job Shop Scheduling; Uncertainty; Earliness; /; Tardiness; Different Due Date Window; Genetic Algorithm; FUZZY PROCESSING TIME; DUEDATE;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The job shop scheduling problem with different due date windows is researched. A mathematical model is presented with the consideration of uncertain processing time which is presented by triangular fuzzy number. Furthermore, a genetic algorithm is developed to solve this problem. The algorithm generates the initial population by the method of integer coding, combining roulette method and elitist strategy is extended in the selection operation. Precedence operation crossover (POX) is used to ensure the feasibility of the offspring. In the end, an example is given to guarantee the validity of the model and algorithm.

引用

页码：1190 / 1194

页数：5

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