文献类型：期刊文献

英文题名：Scheduling distributed flowshops with flexible assembly and set-up time to minimise makespan

作者：Zhang, Guanghui Xing, Keyi Cao, Feng

第一作者：Zhang, Guanghui;张广辉

通信作者：Xing, KY[1];Xing, KY[2]

机构：[1]Xi An Jiao Tong Univ, State Key Lab Mfg Syst Engn, Xian, Shaanxi, Peoples R China;[2]Xi An Jiao Tong Univ, Syst Engn Inst, Xian, Shaanxi, Peoples R China;[3]Guizhou Inst Technol, Sch Sci, Guiyang, Guizhou, Peoples R China

第一机构：Xi An Jiao Tong Univ, State Key Lab Mfg Syst Engn, Xian, Shaanxi, Peoples R China

通信机构：corresponding author), Xi An Jiao Tong Univ, State Key Lab Mfg Syst Engn, Xian, Shaanxi, Peoples R China;corresponding author), Xi An Jiao Tong Univ, Syst Engn Inst, Xian, Shaanxi, Peoples R China.

年份：2018

卷号：56

期号：9

起止页码：3226-3244

外文期刊名：INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH

收录：;EI(收录号：20174704418108);Scopus(收录号：2-s2.0-85034083333);WOS:【SCI-EXPANDED(收录号:WOS:000434401700012)】；

基金：This work was supported by National Natural Science Foundation of China [grant number 61573278].

语种：英文

外文关键词：distributed flowshop scheduling; flexible assembly; set-up time; variable neighbourhood search; particle swarm optimisation

摘要：The scheduling problems under distributed production or flexible assembly settings have achieved increasing attention in recent years. This paper considers scheduling the integration of these two environments and proposes an original distributed flowshop scheduling problem with flexible assembly and set-up time. Distributed production stage is deployed several homogeneous flowshop factories that process the jobs to be assembled into final products in the flexible assembly stage. The objective is to find a schedule, including a production subschedule for jobs and an assembly subschedule for products, to minimise the makespan. Such a scheduling problem involves four successive decisions: assigning jobs to production factories, sequencing jobs at every factory, designating an assembly machine for each product and sequencing products on each assembly machine. The computational model is first established, and then a constructive heuristic (TPHS) and two hybrid metaheuristics (HVNS and HPSO) are proposed. Numerical experiments have been carried out and results validate the algorithmic feasibility and effectiveness. TPHS can obtain reasonable solutions in a shorter time, while metaheuristics can report better solutions using more yet acceptable time. HPSO is statistically comparable yet less robust compared with HVNS for small-scale instances. For the large-scale case, HPSO outperforms HVNS on both effectiveness and robustness.