Hybrid artificial bee colony algorithm with a rescheduling strategy for solving flexible job shop scheduling problems

被引:92
|
作者
Li, Xixing [1 ]
Peng, Zhao [2 ]
Du, Baigang [2 ]
Guo, Jun [2 ]
Xu, Wenxiang [2 ]
Zhuang, Kejia [2 ]
机构
[1] Hubei Univ Technol, Sch Mech Engn, Wuhan 430068, Hubei, Peoples R China
[2] Wuhan Univ Technol, Sch Mech & Elect Engn, Hubei Digital Mfg Key Lab, Wuhan 430070, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
Flexible job shop scheduling; Reschedule strategy; Hybrid artificial bee colony; Cluster grouping; Tabu search; GENETIC ALGORITHM; TABU SEARCH; ABC ALGORITHM; FLOW-SHOP; OPTIMIZATION; MAINTENANCE; CONSTRAINTS; SYSTEM; MODEL;
D O I
10.1016/j.cie.2017.09.005
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This study mainly focuses on flexible job shop scheduling problems (FJSSPs) in a modern manufacturing enterprise that presents a number of different emergencies, such as new jobs inserted, old jobs cancelled, machinery breakdowns. A feasible mathematical model based on a rescheduling strategy has, been constructed as an effective solution. The rescheduling strategy is illustrated by three types of scheduling: reassembling scheduling, intersecting scheduling and inserting scheduling. The objective function is to minimize the maximum completion time (makespan). A hybrid artificial bee colony algorithm (HABC) based on Tabu search (TS) has been developed to solve the model, and a cluster grouping roulette method is proposed to better initialize the population. A crossover operator is introduced for employed bees to improve the exploitation feature. Comparative experiments with other published algorithms have been conducted on well-known benchmark instances, and the analysis results show that the HABC algorithm is efficient and effective. In addition, the proposed algorithm is applied to solve actual FJSSPs in a textile machinery manufacturing enterprise. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:10 / 26
页数:17
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