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Bi-objective scheduling for reentrant hybrid flow shop using Pareto genetic algorithm

Title
Bi-objective scheduling for reentrant hybrid flow shop using Pareto genetic algorithm
Author
정인재
Keywords
Pareto genetic algorithm; NSGA-II; Reentrant hybrid flowshop; MINIMIZING MAKESPAN; SINGLE-MACHINE; LOCAL SEARCH; TARDINESS; MULTIPLE
Issue Date
2011-09
Publisher
PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
Citation
In Computers & Industrial Engineering, Vol.61, No.3 [2011], p529-541
Abstract
This paper deals with a scheduling problem for reentrant hybrid flowshop with serial stages where each stage consists of identical parallel machines. In a reentrant flowshop, a job may revisit any stage several times. Local-search based Pareto genetic algorithms with Minkowski distance-based crossover operator is proposed to approximate the Pareto optimal solutions for the minimization of makespan and total tardiness in a reentrant hybrid flowshop. The Pareto genetic algorithms are compared with existing multi-objective genetic algorithm, NSGA-II in terms of the convergence to optimal solution, the diversity of solution and the dominance of solution. Experimental results show that the proposed crossover operator and local search are effective and the proposed algorithm outperforms NSGA-II by statistical analysis. (C) 2011 Elsevier Ltd. All rights reserved.
URI
https://www.sciencedirect.com/science/article/pii/S0360835211001094?via%3Dihub
ISSN
0360-8352
DOI
10.1016/j.cie.2011.04.008
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > INDUSTRIAL ENGINEERING(산업공학과) > Articles
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