Title :
Hybrid flow shop scheduling using genetic algorithms
Author :
Xiao, Wendong ; Hao, Peifeng ; Zhang, Sen ; Xu, Xinhe
Author_Institution :
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
We investigate the genetic algorithm approach for scheduling hybrid flow shops with minimum makespan as performance measure. The hybrid flow shop problem is characterized as the scheduling of jobs in a flow shop environment where, at any stage, there may exist multiple machines. The algorithm is based on the list scheduling principle by developing job sequences for the first stage and queuing the remaining stages in a FIFO manner. Experiments show that the proposed algorithm outperforms existing heuristic procedures and random search methods
Keywords :
genetic algorithms; production control; queueing theory; genetic algorithms; hybrid flow shops; job sequences; performance measure; production control; queuing theory; scheduling; Flexible manufacturing systems; Fluid flow measurement; Genetic algorithms; Information science; Job shop scheduling; Manufacturing automation; Parallel machines; Processor scheduling; Scheduling algorithm; Search methods;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.860026