DocumentCode
2488249
Title
A Coevolutionary Genetic Based Scheduling Algorithm for stochastic flexible scheduling problem
Author
Gu, Jinwei ; Gu, Xingsheng ; Jiao, Bin
Author_Institution
Dept. of Inf. Sci. & Eng., East China Univ. of Sci. & Technol., Shanghai
fYear
2008
fDate
25-27 June 2008
Firstpage
4160
Lastpage
4165
Abstract
Because traditional genetic algorithm has many limitations on solutions for the combined optimization problems, a coevolutionary genetic based scheduling algorithm (CGBSA) is proposed for solving the stochastic flexible scheduling problem. In CGBSA, the number of sub-population is divided by the number of working procedure. The interaction of all sub-populations is reflected by means of the definition of fitness function. Based on stochastic programming theory and stochastic simulation, a model is presented object to minimize the maximum completion time, in which the processing time is uncertainty. Compared with GA, the simulation results validate the efficiency of the proposed stochastic schedule model and algorithm.
Keywords
evolutionary computation; scheduling; stochastic programming; coevolutionary genetic based scheduling algorithm; stochastic flexible scheduling problem; stochastic programming theory; stochastic simulation; Computational modeling; Evolution (biology); Genetic algorithms; Job shop scheduling; Probability distribution; Processor scheduling; Robustness; Scheduling algorithm; Stochastic processes; Uncertainty; Stochastic flexible scheduling; coevolutionary Genetic Algorithm; stochastic programming; stochastic simulation; uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location
Chongqing
Print_ISBN
978-1-4244-2113-8
Electronic_ISBN
978-1-4244-2114-5
Type
conf
DOI
10.1109/WCICA.2008.4593591
Filename
4593591
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