文献类型：期刊文献

英文题名：Distributed assembly permutation flow-shop scheduling problem with sequence-dependent set-up times using a novel biogeography-based optimization algorithm

作者：Huang, Jialin[1];Gu, Xingsheng[1]

机构：[1]East China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai, Peoples R China

年份：2022

卷号：54

期号：4

起止页码：593

外文期刊名：ENGINEERING OPTIMIZATION

收录：;EI(收录号：20210910014472);WOS:【SCI-EXPANDED(收录号:WOS:000622184900001)】；

基金：This study was financially sponsored by the National Natural Science Foundation of China [grant numbers 61973120, 61573144, 61773165 and 61673175].

语种：英文

外文关键词：Scheduling problem; biogeography-based optimization algorithm; distributed assembly permutation flow shop; sequence-dependent set-up times

摘要：This article proposes a novel biogeography-based optimization (NBBO) algorithm to solve the distributed assembly permutation flow-shop scheduling problem with sequence-dependent set-up times (DAPFSP-SDST). The optimization objective of this problem is minimizing the maximum completion time (makespan). In the initialization phase, NBBO generates two kinds of feasible solutions. Secondly, the linear migration model is replaced with the sinusoidal migration model and a modified product insertion method is performed in the migration phase. Then, in the mutation phase, a job insertion method is used to adjust the processing order of jobs in each product. A local search method based on SDST is combined to jump out of local optima. Finally, simulation experiments based on 540 test instances and comparisons with seven existing algorithms as well as one simple biogeography-based optimization algorithm verify the superiority of NBBO.