Paper Title:
Hybrid Mean Particle Swarm Optimization Algorithm for Permutation Flow Shop Scheduling Problem
  Abstract

This paper presents a new hybrid mean particle swarm optimization algorithm with improved NEH heuristic approach and local search strategies by using an immune mechanism. This hybrid mean particle swarm optimization algorithm is used for permutation flow shop scheduling problems. Finally, twenty-five problems are used to test the performance of the algorithm, the experimental results show that the proposed approach is an effective and practical.

  Info
Periodical
Edited by
Ran Chen
Pages
270-274
DOI
10.4028/www.scientific.net/AMM.44-47.270
Citation
Y. Q. Zhou, Z. X. Huang, Y. L. Du, Q. Q. Gong, "Hybrid Mean Particle Swarm Optimization Algorithm for Permutation Flow Shop Scheduling Problem", Applied Mechanics and Materials, Vols. 44-47, pp. 270-274, 2011
Online since
December 2010
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