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A hybrid scatter search for the partial job shop scheduling problem

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Abstract

This paper presents a special case of the general shop called partial job shop problem. The partial job shop is a more realistic generalization of the mixed shop problem. The problem is formulated as a mixed integer programming model. A scatter search algorithm combined with tabu search and path relinking is used to tackle this problem with makespan criterion. The computational experiments are performed on some problem instances. The results are compared with a lower bound and the effectiveness of the algorithm is shown.

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References

  1. Garey MR, Johnson DS, Sethi R (1976) The complexity of flowshop and job-shop scheduling. Math Oper Res 1:117–129

    Article  MATH  MathSciNet  Google Scholar 

  2. Nowicki E, Smutnicki C (1996) A fast taboo search algorithm for the job shop scheduling problem. Manage Sci 42(6):797–813

    Article  MATH  Google Scholar 

  3. Pezzella F, Merelli E (2000) A tabu search method guided by shifting bottleneck for job shop scheduling problem. Eur J Oper Res 120:297–310

    Article  MATH  MathSciNet  Google Scholar 

  4. Ponnambalam SG, Aravindan P, Rajesh SV (2000) A tabu search algorithm for job shop scheduling. Int J Adv Manuf Technol 16:765–771

    Article  Google Scholar 

  5. Nowicki E, Smutnicki C (2005) An advanced tabu search algorithm for the job shop problem. J Sched 8(2):145–159

    Article  MATH  MathSciNet  Google Scholar 

  6. Watson J, Howe AE, Whitley LD (2006) Deconstructing Nowicki and Smutnicki’s i-TSAB tabu search algorithm for the job-shop scheduling problem. Comput Oper Res 33:2623–2644

    Article  MATH  Google Scholar 

  7. Zhang CY, Li PG, Guan ZL, Rao YQ (2007) A tabu search algorithm with a new neighborhood structure for the job shop scheduling problem. Comput Oper Res 34:3229–3242

    Article  MATH  MathSciNet  Google Scholar 

  8. Balas E, Vazacopoulos A (1998) Guided local search with shifting bottleneck for job shop scheduling. Manage Sci 44(2):262–275

    Article  MATH  Google Scholar 

  9. Zhang CY, Li PG, Rao YQ, Guan ZL (2008) A very fast TS/SA algorithm for the job shop scheduling problem. Comput Oper Res 35:282–294

    Article  MATH  MathSciNet  Google Scholar 

  10. Huang KL, Liao CJ (2008) Ant colony optimization combined with taboo search for the job shop scheduling problem. Comput Oper Res 35:1030–1046

    Article  MATH  MathSciNet  Google Scholar 

  11. Eswaramurthy VP, Tamilarasi A (2009) Hybridizing tabu search with ant colony optimization for solving job shop scheduling problems. Int J Adv Manuf Technol 40:1004–1015

    Article  Google Scholar 

  12. Ponnambalam SG, Jawahar N, Kumar B (2002) Estimation of optimum genetic control parameters for job shop scheduling. Int J Adv Manuf Technol 19:224–234

    Google Scholar 

  13. Wang L, Zheng DZ (2002) A modified genetic algorithm for job shop scheduling. Int J Adv Manuf Technol 20:72–76

    Article  Google Scholar 

  14. Liu TK, Tsai JT, Chou JH (2006) Improved genetic algorithm for the job-shop scheduling problem. Int J Adv Manuf Technol 27:1021–1029

    Article  Google Scholar 

  15. Amirthagadeswaran KS, Arunachalam VP (2006) Improved solutions for job shop scheduling problems through genetic algorithm with a different method of schedule deduction. Int J Adv Manuf Technol 28:532–540

    Article  Google Scholar 

  16. Amirthagadeswaran KS, Arunachalam VP (2007) Enhancement of performance of genetic algorithm for job shop scheduling problems through inversion operator. Int J Adv Manuf Technol 32:780–786

    Article  Google Scholar 

  17. Xu X, Li C (2007) Research on immune genetic algorithm for solving the job-shop scheduling problem. Int J Adv Manuf Technol 34:783–789

    Article  Google Scholar 

  18. Zhang C, Rao Y, Li P (2008) An effective hybrid genetic algorithm for the job shop scheduling problem. Int J Adv Manuf Technol 39:965–974

    Article  Google Scholar 

  19. Wang YM, Yin HL, Wang J (2009) Genetic algorithm with new encoding scheme for job shop scheduling. Int J Adv Manuf Technol 44:977–984

    Article  Google Scholar 

  20. Udomsakdigool A, Kachitvichyanukul V (2008) Multiple colony ant algorithm for job-shop scheduling problem. Int J Prod Res 46:4155–4175

    Article  MATH  Google Scholar 

  21. Pardalos PM, Shylo OV, Vazacopoulos A (2010) Solving job shop scheduling problems utilizing the properties of backbone and “big valley”. Comput Optim Appl. doi:10.1007/s10589-008-9206-5

  22. Rego C, Duarte R (2009) A filter-and-fan approach to the job shop scheduling problem. Eur J Oper Res 194:650–662

    Article  MATH  Google Scholar 

  23. Lin TL, Horng SJ, Kao TW et al (2010) An efficient job-shop scheduling algorithm based on particle swarm optimization. Expert Syst Appl 37:2629–2636

    Article  Google Scholar 

  24. Taillard ED (2009) http://mistic.heig-vd.ch/taillard, November

  25. Brucker P (2004) Scheduling algorithms, 4th edn. Springer, Berlin

    MATH  Google Scholar 

  26. Shakhlevich NV, Sotskov YN, Werner F (2000) Complexity of mixed shop scheduling problems: a survey. Eur J Oper Res 120:343–351

    Article  MATH  MathSciNet  Google Scholar 

  27. Ramudhin A, Marier P (1996) The generalized shifting bottleneck procedure. Eur J Oper Res 93:34–48

    Article  MATH  Google Scholar 

  28. Kis T (2003) Job-shop scheduling with processing alternatives. Eur J Oper Res 151:307–332

    Article  MATH  MathSciNet  Google Scholar 

  29. Debels D, De Reyck B, Leus R, Vanhoucke M (2006) A hybrid scatter search/electromagnetism meta-heuristic for project scheduling. Eur J Oper Res 169:638–653

    Article  MATH  Google Scholar 

  30. Yamashita DS, Armentano VA, Laguna M (2006) Scatter search for project scheduling with resource availability cost. Eur J Oper Res 169:623–637

    Article  MATH  MathSciNet  Google Scholar 

  31. Ranjbar M, De Reyck B, Kianfar F (2009) A hybrid scatter search for the discrete time/resource trade-off problem in project scheduling. Eur J Oper Res 193:35–48

    Article  MATH  Google Scholar 

  32. Laguna M, Marti R (2003) Scatter search—methodology and implementations in C. Kluwer, Boston

    Google Scholar 

  33. Taillard ED (1993) Benchmarks for basic scheduling problems. Eur J Oper Res 64:278–285

    Article  MATH  Google Scholar 

  34. Grabowski J, Wodecki M (2004) A very fast tabu search algorithm for the permutation flow shop problem with makespan criterion. Comput Oper Res 31:1891–1909

    Article  MATH  MathSciNet  Google Scholar 

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Authors and Affiliations

  1. Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran

    Mohammad Mahdi Nasiri & Farhad Kianfar

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  1. Mohammad Mahdi Nasiri
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  2. Farhad Kianfar
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Correspondence to Mohammad Mahdi Nasiri.

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Nasiri, M.M., Kianfar, F. A hybrid scatter search for the partial job shop scheduling problem. Int J Adv Manuf Technol 52, 1031–1038 (2011). https://doi.org/10.1007/s00170-010-2792-2

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  • DOI: https://doi.org/10.1007/s00170-010-2792-2

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