Soft Computing

, Volume 21, Issue 5, pp 1193–1202 | Cite as

A hybrid artificial bee colony algorithm for the job-shop scheduling problem with no-wait constraint

  • Shyam Sundar
  • P. N. Suganthan
  • Chua Tay Jin
  • Cai Tian Xiang
  • Chong Chin Soon
Methodologies and Application


This paper studies a hybrid artificial bee colony (ABC) algorithm for finding high quality solutions of the job-shop scheduling problem with no-wait constraint (JSPNW) with the objective of minimizing makespan among all the jobs. JSPNW is an extension of well-known job-shop scheduling problem subject to the constraint that no waiting time is allowed between operations for a given job. ABC algorithm is a swarm intelligence technique based on intelligent foraging behavior of honey bee swarm. The proposed hybrid approach effectively coordinates the various components of ABC algorithm such as solution initialization, selection and determination of a neighboring solution with the local search in such a way that it leads to high quality solutions for the JSPNW. The proposed approach is compared with the two best approaches in the literature on a set of benchmark instances. Computational results show the superiority of the proposed approach over these two best approaches.


Scheduling Job-shop No-wait Artificial bee colony algorithm Swarm intelligence 


  1. Beasley JE (1990) Or-library: distribution test problems by electronic mail. J Oper Res Soc 41:1069–1072CrossRefGoogle Scholar
  2. Birattari M (2005) Tuning metaheuristics: a machine learning perspective. Springer, BerlinGoogle Scholar
  3. Bożejko W, Makuchowski M (2009) A fast hybrid tabu search algorithm for the no-wait job shop problem. Comput Ind Eng 56:1502–1509Google Scholar
  4. Bożejko W, Makuchowski M (2011) Solving the no-wait job-shop problem by using genetic algorithm with automatic adjustment. Int J Adv Manuf Technol 57:735–752CrossRefGoogle Scholar
  5. Brizuela CA, Zhao Y, Sannomiya N (2001) No-wait and blocking job-shops: Challenging problems for GA’s. In: IEEE international conference on systems, man, and cybernetics. IEEE, New York, pp 2349–2354Google Scholar
  6. Dorn J, Shams R (1996) Scheduling high-grade steelmaking. IEEE Exp 11:28–35CrossRefGoogle Scholar
  7. Framinan JM, Schuster CJ (2006) An enhanced timetabling procedure for the no-wait job shop problem: a complete local search approach. Comput Oper Res 331:1200–1213CrossRefMATHGoogle Scholar
  8. Grabowski J, Pempera J, Smutnicki C (1997) Scheduling in production of concrete wares. In: Operations research proceedings 1996. Springer, Berlin, pp 192–196Google Scholar
  9. Hall N, Sriskandarajah C (1996) A survey on machine scheduling problems with blocking and no-wait in process. Oper Res 44:510–525MathSciNetCrossRefMATHGoogle Scholar
  10. Kamoun H, Sriskandarajah C (1993) The complexity of scheduling jobs in repetitive manufacturing systems. Eur J Oper Res 70:350–364CrossRefMATHGoogle Scholar
  11. Karaboga D (2005) An idea based on honey bee swarm for numerical optimization, technical report—tr06. Erciyes University, TurkeyGoogle Scholar
  12. Karaboga D, Gorkemli B, Ozturk C, Karaboga N (2014) A comprehensive survey: artificial bee colony (abc) algorithm and applications. Artif Intell Rev 42(1):21–57CrossRefGoogle Scholar
  13. Kubiak W (1989) A pseudo-polynomial algorithm for a two-machine no-wait job-shop scheduling problem. Eur J Oper Res 43:267–270MathSciNetCrossRefMATHGoogle Scholar
  14. Lenstra JK, Kan AHGR, Brucker P (1977) Complexity of machine scheduling problems. Ann Discrete Math 1:343–362MathSciNetCrossRefMATHGoogle Scholar
  15. Lixin T, Liu J, Rong A, Yang Z (2000) A mathematical programming model for scheduling steelmaking-continuous casting production. Eur J Oper Res 120:423–435CrossRefMATHGoogle Scholar
  16. Macchiaroli R, Molè S, Riemma S, Trifiletti L (1996) Design and implementation of a tabu search algorithm to solve the no-wait job-shop scheduling problem. In: Proceeding of the CESA96, pp 467–472Google Scholar
  17. Mascis A, Pacciarelli D (2002) Job-shop scheduling with blocking and no-wait constraints. Eur J Oper Res 143:498–517MathSciNetCrossRefMATHGoogle Scholar
  18. Pan JC-H, Huang H-C (2009) A hybrid genetic algorithm for no-wait job shop scheduling problems. Exp Syst Appl 36:5800–5806CrossRefGoogle Scholar
  19. Pan Q-K, Tasgetiren M, Liang Y-C (2008) A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem. Comput Oper Res 35:28072839MathSciNetCrossRefMATHGoogle Scholar
  20. Pan Q-K, Tasgetiren M, Suganthan P, Chua T (2011) A discrete artificial bee colony algorithm for the lot-streaming flow shop scheduling problem. Inf Sci 181:2455–2468MathSciNetCrossRefGoogle Scholar
  21. Pinedo M (1995) Scheduling: theory, algorithms, and systems. Prentice-Hall, NJMATHGoogle Scholar
  22. Reklaitis G (1982) Review of scheduling of process operations. AIChE Symp Ser 78:119–133Google Scholar
  23. Ridge E, Kudenko D (2010) Tuning an algorithm using design of experiments. In: Bartz-Beielstein T, Chiarandini M, Paquete L, Preuss M (ed) Experimental methods for the analysis of optimization algorithms. Springer, Berlin, pp 265–286Google Scholar
  24. Roy B, Sussmann B (1964) Les problèmes d’ordonnancement avec constraintes disjonctives. SEMA, Note D.S., No. 9, ParisGoogle Scholar
  25. Sahni S, Cho Y (1979) Complexity of scheduling shops with no wait in process. Math Oper Res 4:448–457MathSciNetCrossRefMATHGoogle Scholar
  26. Schuster CJ (2006) No-wait job shop scheduling: Tabu search and complexity of subproblems. Math Meth Oper Res 63:473–491MathSciNetCrossRefMATHGoogle Scholar
  27. Schuster CJ, Framinan J (2003) Approximate procedures for no-wait job shop scheduling. Oper Res Lett 31:308–318MathSciNetCrossRefMATHGoogle Scholar
  28. Singh A (2009) An artificial bee colony algorithm for the leaf-constrained minimum spanning tree problem. Appl Soft Comput 9:625–631CrossRefGoogle Scholar
  29. Singh A (2010) A hybrid permutation-coded evolutionary algorithm for the early/tardy scheduling problem. Asia-Pac J Oper Res 27:713–725MathSciNetCrossRefGoogle Scholar
  30. Sriskandarajah C, Ladet P (1986) Some no-wait shops scheduling problems: complexity aspects. Eur J Oper Res 24:424–438MathSciNetCrossRefMATHGoogle Scholar
  31. Sundar S, Singh A (2010) A swarm intelligence approach to the quadratic multiple knapsack problem. In: ICONIP 2010. Lecture notes in computer science, vol 6443. Springer, Berlin, pp 626–633Google Scholar
  32. Sundar S, Singh A (2012) A swarm intelligence approach to the early/tardy scheduling problem. Swarm Evol Computat 4:25–32Google Scholar
  33. Talbi EG (2009) Metaheuristics: from design to implementation. Wiley, New YorkGoogle Scholar
  34. Tasgetiren M, Pan Q-K, Suganthan P, Chen AH-L (2011) A discrete artificial bee colony algorithm for the total flowtime minimization in permutation flow shops. Inf Sci 181:3459–3475MathSciNetCrossRefGoogle Scholar
  35. Valente J, Gonçalves J, Alves R (2006) A hybrid genetic algorithm for the early/tardy scheduling problem. Asia-Pac J Oper Res 23:393–405MathSciNetCrossRefMATHGoogle Scholar
  36. Zhu J, Li X (2012) An effective meta-heuristic for no-wait job shops to minimize makespan. IEEE Trans Autom Sci Eng 9:189–198Google Scholar
  37. Zhu J, Li X, Wang Q (2009) Complete local search with limited memory algorithm for no-wait job shops to minimize makespan. Eur J Oper Res 198:378–386MathSciNetCrossRefMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Department of Computer ApplicationsNational Institute of Technology RaipurRaipurIndia
  2. 2.School of Electrical and Electronic EngineeringNanyang Technological UniversitySingaporeSingapore
  3. 3.Singapore Institute of Manufacturing TechnologySingaporeSingapore

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