Solving the Flow Shop Problem with Limited Buffers Using Differential Evolution
This paper aims to minimize makspan for the flow shop scheduling problem with intermediate buffers using a discrete differential evolution (DDE) algorithm. In the algorithm, we apply job-permutation-based mutation and crossover operators to generate new candidate solutions, and employ an NEH-based initialization method to produce an initial population. Computational simulations and comparisons show that the proposed DDE algorithm generates better results than the existing hybrid genetic algorithm and hybrid particle swarm optimization in terms of solution quality and robustness.
Flow shop Makespan Differential evolution Heuristics
Jun-Hua Duan Guang-Yu Qiao Min Zhang
school of computer science, Liaocheng University, Liaocheng, China China united network communications company limited liaocheng Branch
国际会议
2011 China Control and Decision Conference(2011中国控制与决策会议 CCDC)
四川绵阳
英文
1509-1513
2011-05-23（万方平台首次上网日期，不代表论文的发表时间）