A new approach for permutation flow-shop scheduling problem using league championship algorithm

CIE 2014 - 44th International Conference on Computers and Industrial Engineering and IMSS 2014 - 9th International Symposium on Intelligent Manufacturing and Service Systems, Joint International Symposium on "The Social Impacts of Developments in Information, Manufacturing and Service Systems" - Proceedings

Volumn , Issue , 2014, Pages 881-894

  Sajadi, Seyed Mojtaba ^a   Kashan, Ali Husseinzadeh ^b   Khaledan, Siyavash ^c  

^a UNIVERSITY OF TEHRAN   (Iran)

^b TARBIAT MODARES UNIVERSITY   (Iran)

^c ISLAMIC AZAD UNIVERSITY   (Iran)

Author keywords

Flow shop system; League championship algorithm (LCA); Metaheuristics; Scheduling

Indexed keywords

ALGORITHMS; EVOLUTIONARY ALGORITHMS; GENETIC ALGORITHMS; LIFE CYCLE; MACHINE SHOP PRACTICE; MANUFACTURE; OPTIMIZATION; PARTICLE SWARM OPTIMIZATION (PSO); SCHEDULING ALGORITHMS;

CONTINUOUS OPTIMIZATION; DIFFERENTIAL EVOLUTION ALGORITHMS; FLOW-SHOPS; LEAGUE CHAMPIONSHIP ALGORITHMS; META HEURISTICS; PERMUTATION FLOW SHOPS; PERMUTATION FLOW-SHOP SCHEDULING; SCHEDULING PROBLEM;

SCHEDULING;

EID: 84923873544     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (32)

1. Reddy, S.S., Ramamoorthy, C.V. 1972. On the Flow-shop scheduling problem with no wait in process, Operational Research Quarterly, 23, pp 323-331.
2. Johnson, S.M. 1954. Optimal two- And three- stage production schedules with setup times included, Naval Research Logistics, pp 61-68.
3. Lageweg, B.J., Lenstra, J.K., Rinnooy Kan, A.H.G. 1978. A general bounding scheme for the permutation flow-shop problem, Operations Research, 26, pp 53-67.
4. Moscato, P. 1989. On evolution, search, optimization, genetic algorithms and martial arts: Toward memetic algorithms, C3P Report 826, Caltech Concurrent Computation Program, California Institute of Technology, Pasadena, California.
5. Osman, I.H., Potts, C.N. 1989. Simulated annealing for permutation flow-shop scheduling, OMEGA, 17, pp 551-557.
6. Nowicki, E., Smutnicki, C. 1996. A fast tabu search algorithm for the permutation flow-shop problem, European Journal of Operational Research, 91, pp 160-175.
7. Grabowski, J., Wodecki, M. 2004. A very fast Tabu search algorithm for the permutation flow shop problem with makespan criterion, Computer & Operations Research, 31: pp 1891-1909.
8. Hansen, P., Mladenovic, N. 2001. Variable neighborhood search: principles and applications, European Journal of Operational Research, 130: pp 449-467.
9. Zheng, D. Z., Wang, L. 2003. An effective hybrid heuristic for flow shop scheduling, The International Journal of Advanced Manufacturing Technology, 21(1), pp 38-44.
10. Qian, B., Wang, L., Hu, R., Wang, W.L., Huang, D.X., Wang, X. 2007. A hybrid differential evolution method for permutation flow-shop scheduling, International Journal of Advanced Manufacturing Technology, 38, pp 757-777.
11. Nearchou, A.C., Omirou, S.L. 2006. Differential evolution for sequencing and scheduling optimization, Journal of Heuristics 12, pp 395-411.
12. Wang, L., Pan, Q. K., Suganthan, P. N., Wang, W. H., Wang, Y. M. 2010. A novel hybrid discrete differential evolution algorithm for blocking flow shop scheduling problems, Computers & Operations Research, 37(3), pp 509-520.
13. Tasgetiren, M.F., Liang, W.C., Sevkli, M., Gencyilma, G. 2007. A particle swarm optimization algorithm for makespan and total flowtime minimization in the permutation flowshop sequencing problem, European Journal of Operational Research, 177, pp 1930-1947.
14. Saravanan, M., Noorul Haq, A., Vivekraj, A., Prasad, T. 2008. Performance evaluation of the scatter search method for permutation flowshop sequencing problems, The International Journal of Advanced Manufacturing Technology, 37, pp 1200-1208.
15. Lin, S.W., Ying, K.C. 2009. Applying a hybrid simulated annealing and tabu search approach to non-permutation flowshop scheduling problems, International Journal of Production Research, 47, pp 1411-1424.
16. Débora, P. R., Ernesto, G. B. 2012. Mixed-integer programming models for flowshop scheduling problems minimizing the total earliness and tardiness, Just-in-Time Systems, Springer Optimization and Its Applications, pp 91-105.
17. Varmazyar, M., Salmasi, N. 2012. Sequence-dependent flow shop scheduling problem minimising the number of tardy jobs, International Journal of Production Research, 50, pp 5843-5858.
18. Tran, T.H., Ng, K. M. 2013. A hybrid water flow algorithm for multi-objective flexible flow shop scheduling problems, Engineering Optimization, 45(4), pp 483-502.
19. Husseinzadeh Kashan, A. 2014. League Championship Algorithm (LCA): An algorithm for global optimization inspired by sport championships, Applied Soft Computing, 16, pp 171-200.
20. Husseinzadeh Kashan, A. 2009. League Championship Algorithm: A new algorithm for numerical function optimization, IEEE International Conference of Soft Computing and Pattern Recognition (SoCPaR 2009), Malacca, Malaysia, Dec 4-7, pp 43-48.
21. Husseinzadeh Kashan, A., Karimi, B. 2010. A new algorithm for constrained optimization inspired by the sport league championships, IEEE World Congress on Computational Intelligence (WCCI 2010), Barcelona, Spain, Jul 18-23, pp 487-494.
22. Ayanegui-Santiago, H. 2009. Recognizing team formations in multiagent systems: Applications in robotic soccer, In: Computational Collective Intelligence, Nguyen NT, Kowalczyk R, Chen SM, editors. Semantic Web, Social Networks and Multiagent Systems, ICCCI 2009, pp 163-173.
23. Carling, C. Williams, A.M. Reilly, T. 2006. Handbook of soccer match analysis: A systematic approach to improving performance, Routledge (pp 2-10).
24. Arnold, D.R. Porterfield, R.I. Smith, C.D. 1998. E-SWOT analysis: An extension of a practical tool for small businesses. Available: http://sbaer.uca.edu/Research/sbida/1988/PDF/31.pdf.
25. Husseizadeh Kashan, A. 2011. An efficient algorithm for constrained global optimization and application to mechanical engineering design: League championship algorithm (LCA), Computer-Aided Design, 43, pp 1769-1792.
26. Husseinzadeh Kashan, A., Karimi, B., Jolai, F. 2006. Effective hybrid genetic algorithm for minimizing makespan on a single-batch-processing machine with non-identical job sizes, International Journal of Production Research, 44, pp 2337-2360.
27. Bean, J. C. 1994. Genetic algorithms and random keys for sequencing and optimization, RSA Journal of Computing, 6, pp 154-160.
28. Taillard, E. 1993. Benchmarks for basic scheduling problems. European Journal of Operational Research, 64(2), pp 278-285.
29. Web Reference: http://ina.eivd.ch/collaborateurs/etd/default.htm.
30. Fatih Tasgetiren, M. Liang, Y.C. Sevkli, Y. Gencyilmaz, 2004. Particle swarm optimization algorithm for permutation flowshop sequencing problem, Fourth International Workshop on Ant Algorithms and Swarm Intelligence (ANTS2004), Brussel, Belgium, Sep 3.
31. Fatih Tasgetiren, M. Liang, Y.C. Sevkli, M. Gencyilmaz, 2004. Differential Evolution Algorithm for Permutation Flowshop Sequencing Problem with Makespan Criterion, Available at: http://www.fatihun.edu.tr/msevkli/IMS-DE-FTASGETIREN-LAST.pdf.
32. Zhang, M. Luo, W. Wang, X. 2008. Differential evolution with dynamic stochastic selection for constrained optimization, Information Sciences, 178, pp 3043-3074.