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Hybrid GA-Based Improvement Heuristic with Makespan Criterion for Flow-Shop Scheduling Problems

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Book cover ENTERprise Information Systems (CENTERIS 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 220))

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Abstract

In the paper, we proposed a hybrid improvement heuristic for permutation flow-shop problem based on the idea of evolutionary algorithm. The approach also employs constructive heuristic that gives a good initial solution. Hybrid GA-based improvement heuristic is applied in conjunction with three well-known constructive heuristics, namely CDS, Gupta’s algorithm and Palmer’s Slope Index. We tested our approach on Reeves’ benchmark set of 21 problem instances range from 20 to 75 jobs and 5 to 20 machines. Subsequently, we compared obtained results to the best-known upper-bound solutions.

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References

  1. Pinedo, M.: Scheduling: Theory, Algorithms and Systems. Springer, New Jersey (2008)

    MATH  Google Scholar 

  2. Gupta, J.N.D.: Analysis of Combinatorial Approach to Flowshop Scheduling Problems (1975)

    Google Scholar 

  3. Johnson, S.M.: Optimal Two and Three Stage Production Schedules with Set-Up Times. Naval Research Logistics Quarterly 1, 61–68 (1954)

    Article  MATH  Google Scholar 

  4. Garey, M.R.D., Johnson, D.S., Sethi, R.: The Complexity of Flowshop and Jobshop Scheduling. Mathematics of Operations Research 1, 117–129 (1976)

    Article  MathSciNet  MATH  Google Scholar 

  5. Conway, R.W., Maxwell, W.L., Miller, L.W.: Theory of Scheduling. Addison-Wesley, Reading (1967)

    MATH  Google Scholar 

  6. Hejazi, S.R., Saghafian, S.: Flowshop Scheduling Problems with Makespan Criterion: A Review. International Journal of Production Research 43(14), 2895–2929 (2005)

    Article  MATH  Google Scholar 

  7. Palmer, D.S.: Sequencing Jobs through a Multi-Stage Process in the Minimum Total Time - A Quick Method of Obtaining a Near Optimum. Opers. Res. Q 16, 101–107 (1965)

    Article  Google Scholar 

  8. Campbell, H.G., Dudek, R.A., Smith, M.L.: A Heuristic Algorithm for the n Job, m Machine Sequencing Problem. Management Science 16(10), 630–637 (1970)

    Article  MATH  Google Scholar 

  9. Dannenbring, D.G.: An Evaluation of Flow Shop Sequencing Heuristics. Management Science 23(11), 1174–1182 (1977)

    Article  MATH  Google Scholar 

  10. Brucker, P., Jurisch, B., Sievers, B.: A Branch and Bound Algorithm for the Job Shop Scheduling Problem. Discrete Applied Mathematics 49(1), 109–127 (1994)

    MathSciNet  MATH  Google Scholar 

  11. Gendreau, M., Laporte, G., Semet, F.: A Tabu Search Heuristic for the Undirected Selective Travelling Salesman Problem. European Journal of Operational Research 106(2-3), 539–545 (1998)

    Article  MATH  Google Scholar 

  12. Murata, T., Ishibuchi, H., Tanaka, H.: Genetic algorithms for flowshop scheduling problems. Computers & Industrial Engineering 30(4), 1061–1071 (1996)

    Article  Google Scholar 

  13. Balas, E., Vazacopoulos, A.: Guided Local Search with Shifting Bottleneck for Job Shop Scheduling. Management Science 44(2), 262–275 (1998)

    Article  MATH  Google Scholar 

  14. Blum, C., Sampels, M.: An Ant Colony Optimization Algorithm for Shop Scheduling Problems. Journal of Mathematical Modelling and Algorithms 3(3), 285–308 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  15. Page, E.S.: An approach to scheduling of jobs on the machines. J. Royal Stat. Soc. 23, 484–492 (1961)

    MathSciNet  Google Scholar 

  16. Gupta, J.N.D.: Heuristic Algorithms for Multistage Flowshop Scheduling Problem. AIIE Transactions 4(1), 11–18 (1972)

    Article  Google Scholar 

  17. Nawaz, M.E., Enscore, I., Ham, I.: A Heuristic Algorithm for the m Machine, n Job Flow Shop Sequence Problem. OMEGA 11(1), 91–95 (1983)

    Article  Google Scholar 

  18. Allahverdi, A., Ng, C.T., Cheng, T.C.E., Kovalyov, M.Y.: A Survey of Scheduling Problems with Setup Times or Costs. European Journal of Operational Research 187, 985–1032 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  19. Hendizadeh, S.H., ElMekkawy, T.Y., Wang, G.G.: Bi-Criteria Scheduling of a Flowshop Manufacturing Cell with Sequence Dependent Setup Time. European Journal of Industrial Engineering 1, 391–413 (2007)

    Article  Google Scholar 

  20. Zobolas, G.I., Tarantilis, C.D., Ioannou, G.: Minimizing Makespan in Permutation Flow Shop Scheduling Problems Using a Hybrid Metaheuristic Algorithm. Computers and Operations Research 36(4), 1249–1267 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  21. Ogbu, F.A., Smith, D.K.: The Application of the Simulated Annealing Algorithm to the Solution of the n/m/Cmax Flowshop Problem. Computers & Operations Research 17, 3243–3253 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  22. Taillard, E.: Benchmarks for basic scheduling problems. European Journal of Operational Research 64, 278–285 (1993)

    Article  MATH  Google Scholar 

  23. Nagar, A., Heragu, S.S., Haddock, J.: A Combined Branch-and-Bound and Genetic Algorithm Based Approach for a Flowshop-Scheduling Problem. Annal. Oper. Res. 63, 397–414 (1996)

    Article  MATH  Google Scholar 

  24. Neppalli, V.R., Chen, C.L., Gupta, J.N.D.: Genetic Algorithms for the Two-Stage Bicriteria Flowshop Problem. Eur. J. Oper. Res. 95, 356–373 (1996)

    Article  MATH  Google Scholar 

  25. Engin, O., Doyen, A.: A New Approach to Solve Hybrid Flow Shop Scheduling Problems by Artificial Immune System. Future Generation Computer Systems 20, 1083–1095 (2004)

    Article  Google Scholar 

  26. Ribas, R., Leisten, J.M.: Review and Classification of Hybrid Flow Shop Scheduling Problems from a Production System and a Solutions Procedure Perspective. Computers and Operations Research 37(8), 1439–1454 (2010)

    Article  MathSciNet  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Faculty of Manufacturing Technologies, Technical University of Kosice, Bayerova 1, 08001, Presov, Slovak Republic

    Pavol Semančo & Vladimír Modrák

Authors
  1. Pavol Semančo
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  2. Vladimír Modrák
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Editor information

Editors and Affiliations

  1. Polytechnic Institute of Cávado e Ave, 4750-810, Vila Frescainha S. Martinho, BCL, Portugal

    Maria Manuela Cruz-Cunha

  2. University of Trás-os-Montes e Alto Douro, 5001-801, Vila Real, Portugal

    João Varajão

  3. Birkbeck, University of London, WC1E 7HX, London, UK

    Philip Powell

  4. School of Technology and Management, Polytechnic Institute of Leiria, 2411-901, Leiria, Portugal

    Ricardo Martinho

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© 2011 Springer-Verlag Berlin Heidelberg

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Semančo, P., Modrák, V. (2011). Hybrid GA-Based Improvement Heuristic with Makespan Criterion for Flow-Shop Scheduling Problems. In: Cruz-Cunha, M.M., Varajão, J., Powell, P., Martinho, R. (eds) ENTERprise Information Systems. CENTERIS 2011. Communications in Computer and Information Science, vol 220. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24355-4_2

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  • DOI: https://doi.org/10.1007/978-3-642-24355-4_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24354-7

  • Online ISBN: 978-3-642-24355-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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