A new hybrid ant colony optimization algorithm for solving the no-wait flow shop scheduling problems

被引:131
作者
Engin, Orhan [1 ]
Guclu, Abdullah [1 ]
机构
[1] Konya Tech Univ, Fac Engn & Nat Sci, Dept Ind Engn, TR-42079 Konya, Turkey
关键词
Scheduling; No-wait flow shop; Hybrid ant colony algorithm; Makespan; PARTICLE SWARM OPTIMIZATION; ITERATED GREEDY ALGORITHM; TOTAL COMPLETION-TIME; MAKESPAN CRITERION; GENETIC ALGORITHMS; MINIMIZE MAKESPAN; SETUP TIMES; IN-PROCESS; FLOWSHOPS; SEARCH;
D O I
10.1016/j.asoc.2018.08.002
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 proposes an effective new hybrid ant colony algorithm based on crossover and mutation mechanism for no-wait flow shop scheduling with the criterion to minimize the maximum completion time. The no-wait flow shop is known as a typical NP-hard combinational optimization problem. The hybrid ant colony algorithm is applied to the 192 benchmark instances from literature in order to minimize makespan. The performance of the proposed Hybrid Ant Colony algorithm is compared to the Adaptive Learning Approach and Genetic Heuristic algorithm which are used in previous studies to solve the same set of benchmark problems. The computational experiments show that the proposed Hybrid Ant Colony algorithm provides better results relative to the other algorithms. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:166 / 176
页数:11
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