Integrating flexible preventive maintenance activities into two-stage assembly flow shop scheduling with multiple assembly machines

被引:17
|
作者
Zhang, Zikai [1 ,2 ]
Tang, Qiuhua [1 ,2 ]
机构
[1] Wuhan Univ Sci & Technol, Key Lab Met Equipment & Control Technol, Minist Educ, Wuhan, Peoples R China
[2] Wuhan Univ Sci & Technol, Hubei Key Lab Mech Transmiss & Mfg Engn, Wuhan, Peoples R China
基金
中国国家自然科学基金;
关键词
Multiple assembly machines; Assembly flow shop; Preventive maintenance; Heuristics; Meta-heuristic; ITERATED GREEDY ALGORITHM; ARTIFICIAL BEE COLONY; SETUP TIMES; TARDINESS; MAKESPAN; MINIMIZATION; SYSTEM; COSTS;
D O I
10.1016/j.cie.2021.107493
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, preventive maintenance (PM) activities are incorporated into two-stage assembly flow shop scheduling where m1 dedicated machines in fabrication stage and m2 machines in assembly stage. Each machine is given a new feature maintenance level, whose initial value is determined based on the Weibull probability distribution. To ensure the machines' reliability and production continuity, we need to find a fit product sequence along with PM execution time points. Hence this paper tries to tackle this new integration problem by a mixed integer linear programming model, two heuristics MCMTPM and NEHPM, and a PM-based iterated greedy algorithm (IGPM). IGPM is embedded with a problem-specific solution evaluation and two types of local search methods. The final experimental results show that compared with the other 9 state-of-the-art methods, the proposed IGPM embedded with NEHPM and reference local search generates the best results in all benchmark instances.
引用
收藏
页数:15
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