A Genetic Algorithm for Permutation Flowshop Scheduling With Total Flowtime Criterion
This paper presents a genetic algorithm (GA) for the permutation flow shop scheduling problem with the objective of minimizing total flowtime. An initialization method based on the LR heuristic is used to construct an initial population with a certain level of quality and diversity. A variable-neighborhood-search based local improvement is utilized to refine all the generated solutions in each generation. A comparative evaluation is carried out against some effective algorithms in recent literature. The results show that the proposed GA is very effective for the permutation considered.
Flowshop Genetic algorithm Evolutionary computing Total flowtime
Jun-hua Duan Min Zhang Guang-Yu Qiao Jun-qing Li
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
1514-1517
2011-05-23（万方平台首次上网日期，不代表论文的发表时间）