A novel discrete water wave optimization algorithm for blocking flow-shop scheduling problem with sequence-dependent setup times

被引:55
作者
Shao, Zhongshi [1 ]
Pi, Dechang [1 ,2 ]
Shao, Weishi [1 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Coll Comp Sci & Technol, Nanjing, Jiangsu, Peoples R China
[2] Collaborat Innovat Ctr Novel Software Technol & I, Nanjing, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Flow shop with blocking; Setup times; Scheduling; Heuristic; Metaheuristic; VARIABLE NEIGHBORHOOD SEARCH; ITERATED GREEDY ALGORITHM; TOTAL WEIGHTED TARDINESS; BEE COLONY ALGORITHM; HEURISTIC ALGORITHMS; SHOP PROBLEM; MAKESPAN; FLOWTIME; MACHINE; METAHEURISTICS;
D O I
10.1016/j.swevo.2017.12.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper considers n-job m-machines blocking flow-shop scheduling problem (BFSP) with sequence-dependent setup times (SDST), which has important ramifications in the modern industry. To solve this problem, two efficient heuristics are firstly presented according to the property of the problem. Then, a novel discrete water wave optimization (DWWO) algorithm is proposed. In the proposed DWWO, an initial population with high quality and diversity is constructed based on the presented heuristic and a perturbation procedure. A two-stage propagation is designed to direct the algorithm towards the good solutions. The path relinking technique is employed in refraction phase to help individuals escape from local optima. A variable neighborhood search is developed and embedded in breaking phase to enhance local exploitation capability. A new population updating scheme is applied to accelerate the convergence speed. Moreover, a speedup method is presented to reduce the computational efforts needed for evaluating insertion neighborhood. Finally, extensive numerical tests are carried out, and the results compared to some state-of-the-art metaheuristics demonstrate the effectiveness of the proposed DWWO in solving BFSP with SDST.
引用
收藏
页码:53 / 75
页数:23
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