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Variable Neighborhood Particle Swarm Optimization for Multi-objective Flexible Job-Shop Scheduling Problems

  • Hongbo Liu
  • Ajith Abraham
  • Okkyung Choi
  • Seong Hwan Moon
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4247)

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.

Keywords

Particle Swarm Optimization Completion Time Particle Swarm Optimization Algorithm Large Scale Problem Variable Neighborhood Search 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hongbo Liu
    • 1
    • 2
  • Ajith Abraham
    • 1
    • 3
  • Okkyung Choi
    • 3
    • 4
  • Seong Hwan Moon
    • 4
  1. 1.School of Computer ScienceDalian Maritime UniversityDalianChina
  2. 2.Department of ComputerDalian University of TechnologyDalianChina
  3. 3.School of Computer Science and EngineeringChung-Ang UniversitySeoulKorea
  4. 4.Department of Science and Technology, Education for LifeSeoul National University of EducationSeoulKorea

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