An Adaptive Discrete Particle Swarm Optimization for Job Shop Scheduling with Fuzzy Processing Time and Fuzzy Due Date
This study proposes an adaptive discrete particle swarm optimization to solve the JSSP with fuzzy processing time and fuzzy due-date.The optimization criterion is makespan.Considering the disadvantage of early maturity that particle swarm optimization has in the late stage of searching, this study suggests changing crossover probability in a self-adaptive way in accordance with the aggregation degree of particle swarm, and modifying mutation probability accordingly.It also proposes to improve algorithm performance by selecting the better on the basis of probability and to carry out the mutation based on processing block to skip out the local maximum.Simulating results for some benchmark problems prove the effectiveness and feasibility of the proposed algorithms.
adaptive discrete particle swarm optimization job shop scheduling problem fuzzy processing time fuzzy due date processing block mutation
Shufeng Wang Xiaocheng Xiao Fei Li
School of Electrical Engineering Zhengzhou University Zhengzhou,China
国际会议
太原
英文
399-403
2011-02-26（万方平台首次上网日期，不代表论文的发表时间）