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
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;
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
DOI :
10.1109/WCICA.2008.4593591