Abstract
This paper presents a particle swarm optimization algorithm (PSO) to solve the permutation flowshop sequencing problem (PFSP) with makespan criterion. Simple but very efficient local search based on the variable neighborhood search (VNS) is embedded in the PSO algorithm to solve the benchmark suites in the literature. The results are presented and compared to the best known approaches in the literature. Ultimately, a total of 195 out of 800 best-known solutions in the literature is improved by the VNS version of the PSO algorithm.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Abido, M.A.: Optimal power flow using particle swarm optimization. Electrical Power and Energy Systems 24, 563–571 (2002)
Bean, J.C.: Genetic algorithm and random keys for sequencing and optimization. ORSA journal on computing 6(2), 154–160 (1994)
Eberhart, R.C., Kennedy, J.: A new optimizer using particle swarm theory. In: Proc. of the Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan, pp. 39–43 (1995)
Framinan, J.M., Leisten, R.: An efficient constructive heuristic for flowtime minimisation in permutation flow shops. Omega 31, 311–317 (2003)
Grabowski, J., Wodecki, M.: A very fast tabu search algorithm for the permutation flowshop problem with makespan criterion. Computers and Operations Research 31(11), 1891–1909 (2004)
Hu, X., Eberhard, R.C., Shi, Y.: Swarm Intelligence for Permutation optimization: A case study of n-Queens problem. In: Proc. of the 2003 IEEE Swarm Intelligence Symposium, Indianapolis, IN, pp. 243–246 (2003)
Kennedy, J., Eberhart, R.C., Shi, Y.: Swarm intelligence. Morgan Kaufmann, San Mateo (2001)
Mladenovic, N., Hansen, P.: Variable Neighborhood Search. Computers and Operations Research 24, 1097–1100 (1997)
Nawaz, M., Enscore Jr, E., Ham, I.: A heuristic algorithm for the m-machine, n-job flow shop sequencing problem. Omega 11(1), 91–95 (1983)
Onwubolu, G.C., Clerc, M.: Optimal operating path for automated drilling operations by a new heuristic approach using particle swarm optimisation. International Journal of Production Research 42(3), 473–491 (2004)
Nowicki, E., Smutnicki, C.: A fast tabu search algorithm for the permutation flowshop problem. European Journal of Operational Research 91, 160–175 (1996)
Osman, I., Potts, C.: Simulated annealing for permutation flow shop scheduling. Omega 17(6), 551–557 (1989)
Reeves, C., Yamada, T.: Genetic algorithms, path relinking and the flowshop sequencing problem. Evolutionary Computation 6, 45–60 (1998)
Rinnooy Kan, A.H.G.: Machine scheduling problems: Classification, complexity and computations, Nijhoff, The Hague (1976)
Salman, A., Ahmad, I., Al-Madani, S.: Particle swarm optimization for task assignment problem. Microprocessors and Microsystems 26, 363–371 (2003)
Stützle, T.: Applying iterated local search to the permutation flowshop problem, Technical Report, AIDA-98-04, Darmstad University of Technology, Darmstad, Germany (1998)
Stützle, T.: An ant approach to the flowshop problem. In: Proc. of EUFIT 1998, pp. 1560–1564 (1998)
Taillard, E.: Benchmarks for basic scheduling problems. European Journal of Operational Research 64, 278–285 (1993)
Tasgetiren, M.F., Sevkli, M., Liang, Y.-C., Gencyilmaz, G.: Particle swarm optimization algorithm for single machine total weighted tardiness problem. In: Proc. of the 2004 Congress on Evolutionary Computation (2004) (to appear)
Watson, J.P., Barbulescu, L., Whitley, L.D., Howe, A.E.: Contrasting structured and Random Permutation Flowshop Scheduling Problems: Search space Topology and Algorithm Performance. ORSA Journal of Computing 14(2), 98–123 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tasgetiren, M.F., Sevkli, M., Liang, YC., Gencyilmaz, G. (2004). Particle Swarm Optimization Algorithm for Permutation Flowshop Sequencing Problem. In: Dorigo, M., Birattari, M., Blum, C., Gambardella, L.M., Mondada, F., Stützle, T. (eds) Ant Colony Optimization and Swarm Intelligence. ANTS 2004. Lecture Notes in Computer Science, vol 3172. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28646-2_38
Download citation
DOI: https://doi.org/10.1007/978-3-540-28646-2_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22672-7
Online ISBN: 978-3-540-28646-2
eBook Packages: Springer Book Archive