A Coevolutionary Genetic Based Scheduling Algorithm for stochastic flexible scheduling problem
Chongqing（2008）
摘要
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.
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关键词
stochastic flexible scheduling problem,scheduling,evolutionary computation,stochastic simulation,stochastic flexible scheduling,coevolutionary genetic algorithm,uncertainty,stochastic programming theory,coevolutionary genetic based scheduling algorithm,stochastic programming,optimization problem,robustness,stochastic processes,computational modeling,job shop scheduling,probability distribution,genetic algorithm,programming,scheduling algorithm,genetic algorithms,fitness function,mathematical model,scheduling problem
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