DocumentCode
2308793
Title
Hybrid GA-based metaheuristics for production planning and scheduling optimization in intelligent flow-shop manufacturing systems
Author
Semanco, Pavol ; Modrak, Vladimir
Author_Institution
Dept. of Manuf. Manage., Tech. Univ. of Kosice, Presov, Slovakia
fYear
2011
fDate
23-25 June 2011
Firstpage
381
Lastpage
385
Abstract
The paper introduces a proposal of three-metaheuristic versions to optimize flow-shop problem emphasized on total flow time criterion in Intelligent Manufacturing Systems. The approach employs constructive heuristic, namely CDS, Gupta´s algorithm, and Palmer´s Slope Index, in conjunction with GA-based metaheuristic. The approach is tested on Reeves´ benchmark set of 21 flow-shop problems range from 20 to 75 jobs and 5 to 20 machines.
Keywords
flow production systems; genetic algorithms; intelligent manufacturing systems; production planning; scheduling; Gupta´s algorithm; Palmer´s slope index; hybrid GA-based metaheuristics; intelligent flow-shop manufacturing systems; optimization; production planning; production scheduling; total flow time criterion; Genetic algorithms; Heuristic algorithms; Job shop scheduling; Optimal scheduling; Processor scheduling; Schedules; GA; IMS; genetic algorithm; metaheuristic; scheduling;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Engineering Systems (INES), 2011 15th IEEE International Conference on
Conference_Location
Poprad
Print_ISBN
978-1-4244-8954-1
Type
conf
DOI
10.1109/INES.2011.5954777
Filename
5954777
Link To Document