The improved genetic algorithm for job-shop scheduling problem with process sequence flexibility
This paper is focused on a new scheduling problem considering the sequence flexibility in classical job shop scheduling problem (SFJSP) that is very practical in most realistic situations.SFJSP consists of two sub-problems which are determining the sequence of flexible operations of each job and sequencing all the operations on the machines according to the determined operation sequence.An improved genetic algorithm (IGA) is proposed to solve this problem to minimize makespan.An improved chromosome encoding schema is proposed for IGA,in which sequence-based representation segment is added to the general operation-based representation segment.The corresponding crossover and mutation operators are designed to ensure the generation of feasible offspring chromosome for SFJSP.The effectiveness and efficiency of the proposed algorithm is tested by computational experiments on four practical instances of a bearing manufacturing corporation.
component formatting style styling insert
MA Xueli CAO Debi LIU Xiaobing
School of Management,Dalian University of Technology,Dalian,China,116024 Faculty of Science and Technology,Keio University,Tokyo,Japanese
国际会议
大连
英文
716-723
2013-06-29（万方平台首次上网日期，不代表论文的发表时间）