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Variable neighborhood particle swarm optimization for multi-objective flexible job-shop scheduling problems

Authors
Liu, HongboAbraham, AjithChoi, OkkyungMoon, Seong Hwan
Issue Date
2006
Publisher
SPRINGER-VERLAG BERLIN
Citation
SIMULATED EVOLUTION AND LEARNING, PROCEEDINGS, v.4247, pp 197 - 204
Pages
8
Journal Title
SIMULATED EVOLUTION AND LEARNING, PROCEEDINGS
Volume
4247
Start Page
197
End Page
204
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/65450
DOI
10.1007/11903697_26
ISSN
0302-9743
1611-3349
Abstract
This paper introduces a hybrid metaheuristic, the Variable Neighborhood Particle Swarm Optimization (VNPSO), consisting of a combination of the Variable Neighborhood Search (VNS) and Particle Swarm Optimization (PSO). The proposed VNPSO method is used for solving the multi-objective Flexible Job-shop Scheduling Problems (FJSP). The details of implementation for the multi-objective FJSP and the corresponding computational experiments are reported. The results indicate that the proposed algorithm is an efficient approach for the multi-objective FJSP, especially for large scale problems.
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