Paper Info
Title
Analysis Of Double-Resource Flexible Job Shop Scheduling Problem Based On Genetic Algorithm
Abstract
The classic job shop scheduling problem mainly focuses on one kind of manufacturing resources, such as machine tools, and etc. But the job shop scheduling in practical production activities always needs to consider the constraints of different manufacturing resources. In this paper, a double resource flexible job shop scheduling problem (DFJSSP) is presented. Both machines and workers are considered in the process of job shop scheduling in this DFJSSP. And a genetic algorithm (GA) is used to solve this problem, in which a new well designed three-layer chromosome encoding method has been adopted and some effective crossover and mutation operators are designed. Finally, a case study is used to validate the method.
Year
Venue
Keywords
2018
2018 IEEE 15TH INTERNATIONAL CONFERENCE ON NETWORKING, SENSING AND CONTROL (ICNSC)
double-resource, shop scheduling problem, genetic algorithm
Field
DocType
ISSN
Crossover,Job shop scheduling,Industrial engineering,Chromosome encoding,Job shop scheduling problem,Computer science,Control engineering,Genetic algorithm,Mutation operator,Machine tool,Encoding (memory)
Conference
1810-7869
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Chao Peng100.34
Yiling Fang200.68
Ping Lou355.54
Junwei Yan401.01