Improved cuckoo search algorithm for hybrid flow shop scheduling problems to minimize makespan

被引：150
作者：
Marichelvam, M. K. [1 ]
Prabaharan, T. [2 ]
Yang, X. S. [3 ]
机构：
[1] Kamaraj Coll Engn & Technol, Dept Mech Engn, Virudunagar 626001, Tamil Nadu, India
[2] Mepco Schlenk Engn Coll, Dept Mech Engn, Sivakasi 626005, Tamil Nadu, India
[3] Middlesex Univ, Sch Sci & Technol, London NW4 4BT, England
来源：
APPLIED SOFT COMPUTING | 2014年 / 19卷
关键词：
Hybrid flow shop (HFS); Scheduling; NP-hard; Improved cuckoo search (ICS); Metaheuristics; PARTICLE SWARM OPTIMIZATION; MULTIPLE PROCESSORS; GENETIC ALGORITHM; BOUND ALGORITHM; 2-STAGE; HEURISTICS; BRANCH; FLOWSHOPS;
D O I：
10.1016/j.asoc.2014.02.005
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The multistage hybrid flow shop (HFS) scheduling problems are considered in this paper. Hybrid flowshop scheduling problems were proved to be NP-hard. A recently developed cuckoo search (CS) metaheuristic algorithm is presented in this paper to minimize the makespan for the HFS scheduling problems. A constructive heuristic called NEH heuristic is incorporated with the initial solutions to obtain the optimal or near optimal solutions rapidly in the improved cuckoo search (ICS) algorithm. The proposed algorithm is validated with the data from a leading furniture manufacturing company. Computational results show that the ICS algorithm outperforms many other metaheuristics. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码：93 / 101
页数：9
相关论文
共 54 条
123456