Variable neighborhood particle swarm optimization for multi-objective flexible job-shop scheduling problems
- Authors
- Liu, Hongbo; Abraham, Ajith; Choi, Okkyung; Moon, 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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Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
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