Skip to main content

Advertisement

SpringerLink
Log in

Uniform parallel batch machines scheduling considering transportation using a hybrid DPSO-GA algorithm

  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

This paper investigates coordinated scheduling on uniform parallel batch machines with batch transportation. Jobs are characterized by different processing time and sizes, and they are first delivered to manufacturers in batches and then processed on the uniform parallel batch machines. The manufacturers are distributed in different geographic zones and there exists one parallel batch machine in each manufacturer. A mixed integer programming model is developed for the studied problem, and its objective is to minimize the makespan. In addition, the structural properties of the problem are analyzed. A hybrid algorithm combining the merits of discrete particle swarm optimization (DPSO) and genetic algorithm (GA) is proposed to solve this problem. In the hybrid algorithm, a heuristic and a local search strategy are introduced. Finally, computational experiments are conducted and the results show that the proposed hybrid algorithm can effectively and efficiently solve the problem within a reasonable time, particularly in large-scale instances.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Pei J, Pardalos PM, Liu X, Fan W, Yang S (2015) Serial batching scheduling of deteriorating jobs in a two-stage supply chain to minimize the makespan. Eur J Oper Res 244(1):13–25

    Article  MathSciNet  MATH  Google Scholar 

  2. Uzsoy R (1994) Scheduling a single batch processing machine with non-identical job sizes. Int J Prod Res 32(7):1615–1635

    Article  MATH  Google Scholar 

  3. Ikura Y, Gimple M (1986) Efficient scheduling algorithms for a single batch processing machine. Oper Res Lett 5(2):61–65

    Article  MathSciNet  MATH  Google Scholar 

  4. Ghazvini FJ, Dupont L (1998) Minimizing mean flow times criteria on a single batch processing machine with non-identical jobs sizes. Int J Prod Econ 55(3):273–280

    Article  Google Scholar 

  5. Zhang X, Li X, Wang J (2016) Local search algorithm with path relinking for single batch-processing machine scheduling problem. Neural Comput & Applic. doi:10.1007/s00521-016-2339-z.

    Google Scholar 

  6. Damodaran P, Chang PY (2008) Heuristics to minimize makespan of parallel batch processing machines. Int J Adv Manuf Technol 37(9–10):1005–1013

    Article  Google Scholar 

  7. Ozturk O, Espinouse ML, Mascolo MD, Gouin A (2012) Makespan minimisation on parallel batch processing machines with non-identical job sizes and release dates. Int J Prod Res 50(20):6022–6035

    Article  Google Scholar 

  8. Kashan AH, Karimi B, Jenabi M (2008) A hybrid genetic heuristic for scheduling parallel batch processing machines with arbitrary job sizes. Comput Oper Res 35(4):1084–1098

    Article  MATH  Google Scholar 

  9. Malve S, Uzsoy R (2007) A genetic algorithm for minimizing maximum lateness on parallel identical batch processing machines with dynamic job arrivals and incompatible job families. Comput Oper Res 34(10):3016–3028

    Article  MathSciNet  MATH  Google Scholar 

  10. Belkaid F, Sari Z, Yalaoui F (2013) A hybrid genetic algorithm for parallel machine scheduling problem with consumable resources. In: Proceedings of the 2013 I.E. international conference on control, decision and information technologies, pp. 143–148

  11. Chang PY, Damodaran P, Melouk S (2004) Minimizing makespan on parallel batch processing machines. Int J Prod Res 42(19):4211–4220

    Article  Google Scholar 

  12. Abedi M, Seidgar H, Fazlollahtabar H, et al. (2015) Bi-objective optimization for scheduling the identical parallel batch-processing machines with arbitrary job sizes, unequal job release times and capacity limits. Int J Prod Res 53(6):1680–1711

    Article  Google Scholar 

  13. Bilyk A, Mönch L, Almeder C (2014) Scheduling jobs with ready times and precedence constraints on parallel batch machines using metaheuristics. Comput Ind Eng 78:175–185

    Article  Google Scholar 

  14. Xu S, Bean JC (2007) A genetic algorithm for scheduling parallel non-identical batch processing machines. In: Proceedings of the 2007 I.E. symposium on computational intelligence in scheduling, pp. 143–150

  15. Damodaran P, Diyadawagamage DA, Ghrayeb O, Vélez-Gallego MC (2012) A particle swarm optimization algorithm for minimizing makespan of nonidentical parallel batch processing machines. Int J Adv Manuf Technol 58(9–12):1131–1140

    Article  Google Scholar 

  16. Li X, Chen H, Du B, Tan Q (2013) Heuristics to schedule uniform parallel batch processing machines with dynamic job arrivals. Int J Comput Integr Manuf 26(5):474–486

    Article  Google Scholar 

  17. Li X, Huang Y, Tan Q, Chen H (2013) Scheduling unrelated parallel batch processing machines with non-identical job sizes. Comput Oper Res 40(12):2983–2990

    Article  MathSciNet  MATH  Google Scholar 

  18. Zhou S, Liu M, Chen H, et al. (2016) An effective discrete differential evolution algorithm for scheduling uniform parallel batch processing machines with non-identical capacities and arbitrary job sizes. Int J Prod Econ 179:1–11

    Article  Google Scholar 

  19. Lu L, Yuan J (2008) Unbounded parallel batch scheduling with job delivery to minimize makespan. Oper Res Lett 36(4):477–480

    Article  MathSciNet  MATH  Google Scholar 

  20. Pei J, Liu X, Pardalos PM, et al. (2015) Solving a supply chain scheduling problem with non-identical job sizes and release times by applying a novel effective heuristic algorithm. Int J Syst Sci 47(4):765–776

    Article  MathSciNet  MATH  Google Scholar 

  21. Pei J, Liu X, Pardalos PM, Fan W, Yang S, Wang L (2014) Application of an effective modified gravitational search algorithm for the coordinated scheduling problem in a two-stage supply chain. Int J Adv Manuf Technol 70(1–4):335–348

    Article  Google Scholar 

  22. Li S, Yuan J, Fan B (2011) Unbounded parallel-batch scheduling with family jobs and delivery coordination. Inf Process Lett 111(12):575–582

    Article  MathSciNet  MATH  Google Scholar 

  23. Cheng B, Yang Y, Hu X (2016) Supply chain scheduling with batching, production and distribution. Int J Comput Integr Manuf 29(3):251–262

    Article  Google Scholar 

  24. Wan L, Zhang A (2014) Coordinated scheduling on parallel machines with batch delivery. Int J Prod Econ 150:199–203

    Article  Google Scholar 

  25. Gong H, Chen D, Xu K (2014) Parallel-batch scheduling and transportation coordination with waiting time constraint. Sci World J. doi:10.1155/2014/356364.

    Google Scholar 

  26. Kashan AH, Karimi B (2009) A discrete particle swarm optimization algorithm for scheduling parallel machines. Comput Ind Eng 56(1):216–223

    Article  Google Scholar 

  27. Lin YK (2013) Particle swarm optimization algorithm for unrelated parallel machine scheduling with release dates. Math Probl Eng 34(1):130–137

    MathSciNet  Google Scholar 

  28. Yilmaz Eroglu D, Ozmutlu HC, Ozmutlu S (2014) Genetic algorithm with local search for the unrelated parallel machine scheduling problem with sequence-dependent set-up times. Int J Prod Res 52(19):5841–5856

    Article  Google Scholar 

  29. Balin S (2011) Non-identical parallel machine scheduling using genetic algorithm. Expert Syst Appl 38(6):6814–6821

    Article  Google Scholar 

  30. Liu LL, Hu RS, Hu XP, Zhao GP, Wang S (2014) A hybrid PSO-GA algorithm for job shop scheduling in machine tool production. Int J Prod Res 1–27

  31. Yu M, Zhang Y, Chen K, Zhang D (2015) Integration of process planning and scheduling using a hybrid GA/PSO algorithm. Int J Adv Manuf Technol 78(1–4):583–592

    Article  Google Scholar 

  32. Graham RL, Lawler EL, Lenstra JK, Kan AR (1979) Optimization and approximation in deterministic sequencing and scheduling: a survey. Ann Discret Math 5:287–326

    Article  MathSciNet  MATH  Google Scholar 

  33. Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of the 1995 I.E. international conference on neural networks, pp. 1942–1948

  34. Spears WM, Jong KAD (1991) On the virtues of parameterized uniform crossover. In: Proceedings of the 4th international conference on genetic algorithm, pp. 230–236

Download references

Author information

Authors and Affiliations

  1. School of Management, Hefei University of Technology, Hefei, China

    Lu Jiang, Jun Pei, Xinbao Liu & Xiaofei Qian

  2. Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education, Hefei, China

    Lu Jiang & Xinbao Liu

  3. Center for Applied Optimization, Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA

    Jun Pei, Panos M. Pardalos & Xiaofei Qian

  4. Faculty of Science, Hong Kong Baptist University, Hong Kong, China

    Yunjie Yang

Authors
  1. Lu Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jun Pei
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xinbao Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Panos M. Pardalos
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yunjie Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Xiaofei Qian
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Jun Pei or Xinbao Liu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jiang, L., Pei, J., Liu, X. et al. Uniform parallel batch machines scheduling considering transportation using a hybrid DPSO-GA algorithm. Int J Adv Manuf Technol 89, 1887–1900 (2017). https://doi.org/10.1007/s00170-016-9156-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-016-9156-5

Keywords

Search

Navigation