共 71 条
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.
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页码:53 / 75
页数:23
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