An improved hybrid Cuckoo Search (IHCS) metaheuristics algorithm for permutation flow shop scheduling problems

被引：45
|
作者：
Marichelvam, M. K. [1 ]
机构：
[1] Kamaraj Coll Engn & Technol, Dept Mech Engn, Virudunagar 626001, Tamil Nadu, India
来源：
INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION | 2012年 / 4卷 / 04期
关键词：
flow shop; scheduling; makespan; non-deterministic polynomial time hard; NP-hard; heuristics; metaheuristics; improved hybrid Cuckoo Search; IHCS; PARTICLE SWARM OPTIMIZATION;
D O I：
10.1504/IJBIC.2012.048061
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Permutation flow shop scheduling problems with makespan minimisation are considered in this paper. Flow shop scheduling is one important type of scheduling problems for the past several decades. Flow shop scheduling problems are non-deterministic polynomial time hard (NP-hard) problems. Hence the exact methods can not be used to solve these problems. Many heuristics and metaheuristics were addressed in the literature to solve the flow shop scheduling problems. Cuckoo Search is a recently developed metaheuristics algorithm. The efficiency of the algorithm may decrease as the parameters of the Cuckoo Search are constant. Hence an improved hybrid Cuckoo Search (IHCS) algorithm is developed in the present work to solve the permutation flow shop scheduling problems. The proposed algorithm has been implemented for some benchmark problems in the literature and the results are compared with some other metaheuristics algorithms.
引用
收藏
页码：200 / 205
页数：6
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