A particle swarm optimization approach for permutation flow shop scheduling problem
Assistant Professor, Department of Mechanical Engineering, National Institute of Technology Calicut, Kozhikode
673601, Kerala, India
2 Senior Lecturer, Department of Mechanical Engineering, MEA Engineering College, Perinthalmanna 679325, Kerala, India
3 Research Scholar, Department of Mechanical Engineering, National Institute of Technology Calicut, Kozhikode 673601, Kerala, India
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Accepted: 5 November 2013
Flow shop scheduling problem (FSSP) is a combinatorial optimization problem. This work, with the objective of optimizing the makespan of an FSSP uses a particle swarm optimization (PSO) approach. The problems are tested on Taillard’s benchmark problems. The results of Nawaz, Encore and Ham (NEH) heuristic are initialized to the PSO to direct the search into a quality space. Variable neighbourhood search (VNS) is employed to overcome the early convergence of the PSO and helps in global search. The results are compared with standalone PSO, traditional heuristics and the Taillard’s upper bounds. Five problem set are taken from Taillard’s benchmark problems and are solved for various problem sizes. Thus a total of 35 problems are solved. The experimental results show that the solution quality of FSSP can be improved if the search is directed in a quality space based on the proposed PSO approach (PSO-NEH-VNS).
Key words: Makespan / Flow shop scheduling / Particle swarm optimization / Variable neighbourhood search
© T. Radha Ramanan et al., Published by EDP Sciences, 2014
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.