Skip to main content

Advertisement

SpringerLink
Log in

Local search algorithm with path relinking for single batch-processing machine scheduling problem

  • Original Article
  • Published:
Neural Computing and Applications Aims and scope Submit manuscript

Abstract

The single batch-processing machine problem is to minimize makespan, which has broad applications, including engineering fundamentals and theoretical background. The machine can process several jobs as a batch simultaneously, and every job has three different attributes: job size, processing time, and job arrival. In this paper, a hybrid local search algorithm with path relinking (LP) is devised to solve the problem. We not only generate an optimal initial solution firstly but also pay more attention to improving the solution quality. Three kinds of local searches are applied to enhance the diversity of solutions; the path relinking is adopted to explore better solutions through local tracks connecting the current solution and the best in the elite set. With these approaches, it can keep a balanced rate between exploratory and exploitative capacity. Computational experiments on 40 benchmark instances indicate that LP has the superior convergence and robust performance and it surpasses the current state-of-the-art methods such as genetic algorithm and ant colony optimization, especially for large 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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Wang HK, Chien CF, Gen M (2015) An algorithm of multi-subpopulation parameters with hybrid estimation of distribution for semiconductor scheduling with constrained waiting time. IEEE T Semiconduct M 28(3):353–366

    Article  Google Scholar 

  2. Jain N, Menache I, Naor JS, Yaniv J (2015) Near-optimal scheduling mechanisms for deadline-sensitive jobs in large computing clusters. ACM Trans Parallel Comput 2(1):3

    Article  Google Scholar 

  3. Li X, Li M (2015) Multiobjective local search algorithm-based decomposition for multiobjective permutation flow shop scheduling problem. IEEE Trans Eng Manag 62(4):544–557

    Article  Google Scholar 

  4. Li X, Zhang X, Yin M, Wang J (2015) A genetic algorithm for the distributed assembly permutation flowshop scheduling problem. 2015 IEEE congress on in evolutionary computation (CEC). pp 3096–3101

  5. Wang GG, Deb S, Thampi SM (2016). A Discrete Krill Herd Method with multilayer coding strategy for flexible job-shop scheduling problem. In: Intelligent systems technologies and applications. pp 201–215

  6. Nguyen S, Zhang M, Johnston M, Tan KC (2015) Automatic programming via iterated local search for dynamic job shop scheduling. IEEE Trans Cybern 45(1):1–14

    Article  Google Scholar 

  7. Maguluri ST, Srikant R (2014) Scheduling jobs with unknown duration in clouds. IEEE/ACM Trans Netw 22(6):1938–1951

    Article  Google Scholar 

  8. Alidaee B, Li H (2014) Parallel machine selection and job scheduling to minimize sum of machine holding cost, total machine time costs, and total tardiness costs. IEEE Trans Autom Sci Eng 11(1):294–301

    Article  Google Scholar 

  9. Gopinadh V, Singh A (2015) Swarm intelligence approaches for cover scheduling problem in wireless sensor networks. Int J Bio-Inspir Comput 7(1):50–61

    Article  Google Scholar 

  10. Karthikeyan S, Asokan P, Nickolas S, Page T (2015) A hybrid discrete firefly algorithm for solving multi-objective flexible job shop scheduling problems. Int J Bio-Inspir Comput 7(6):386–401

    Article  Google Scholar 

  11. Hao XC, Wu JZ, Chien CF, Gen M (2014) The cooperative estimation of distribution algorithm: a novel approach for semiconductor final test scheduling problems. J Intel Manuf 25(5):867–879

    Article  Google Scholar 

  12. Allahverdi A, Ng CT, Cheng TE, Kovalyov MY (2008) A survey of scheduling problems with setup times or costs. Eur J Oper Res 187(3):985–1032

    Article  MathSciNet  MATH  Google Scholar 

  13. Ruiz R, Vázquez-Rodríguez JA (2010) The hybrid flow shop scheduling problem. Eur J Oper Res 205(1):1–18

    Article  MathSciNet  MATH  Google Scholar 

  14. Ribas I, Leisten R, Framiñan JM (2010) Review and classification of hybrid flow shop scheduling problems from a production system and a solutions procedure perspective. Comput Oper Res 37(8):1439–1454

    Article  MathSciNet  MATH  Google Scholar 

  15. Jungwattanakit J, Reodecha M, Chaovalitwongse P, Werner F (2009) A comparison of scheduling algorithms for flexible flow shop problems with unrelated parallel machines, setup times, and dual criteria. Comput Oper Res 36(2):358–378

    Article  MathSciNet  MATH  Google Scholar 

  16. Nong Q, Yuan J, Fu R, Lin L, Tian J (2008) The single-machine parallel-batching on-line scheduling problem with family jobs to minimize makespan. Int J Prod Econ 111(2):435–440

    Article  Google Scholar 

  17. Costa A, Cappadonna FA, Fichera S (2014) A novel genetic algorithm for the hybrid flow shop scheduling with parallel batching and eligibility constraints. Int J Adv Manuf Technol 75(5–8):833–847

    Article  Google Scholar 

  18. Malapert A, Guéret C, Rousseau LM (2012) A constraint programming approach for a batch processing problem with non-identical job sizes. Eur J Oper Res 221(3):533–545

    Article  MathSciNet  MATH  Google Scholar 

  19. Lee YH, Lee YH (2013) Minimising makespan heuristics for scheduling a single batch machine processing machine with non-identical job sizes. Int J Prod Res 51(12):3488–3500

    Article  Google Scholar 

  20. Al-Salamah M (2015) Constrained binary artificial bee colony to minimize the makespan for single machine batch processing with non-identical job sizes. Appl Soft Comput 29:379–385

    Article  Google Scholar 

  21. Jia ZH, Leung JYT (2014) An improved meta-heuristic for makespan minimization of a single batch machine with non-identical job sizes. Comput Oper Res 46:49–58

    Article  MathSciNet  MATH  Google Scholar 

  22. Wu CC, Liu CL (2010) Minimizing the makespan on a single machine with learning and unequal release times. Comput Ind Eng 59(3):419–424

    Article  Google Scholar 

  23. Yao S, Jiang Z, Li N (2012) A branch and bound algorithm for minimizing total completion time on a single batch machine with incompatible job families and dynamic arrivals. Comput Oper Res 39(5):939–951

    Article  MathSciNet  MATH  Google Scholar 

  24. Chou FD, Chang PC, Wang HM (2006) A hybrid genetic algorithm to minimize makespan for the single batch machine dynamic scheduling problem. Int J Adv Manuf Technol 31(3–4):350–359

    Article  Google Scholar 

  25. Xu R, Chen H, Li X (2012) Makespan minimization on single batch-processing machine via ant colony optimization. Comput Oper Res 39(3):582–593

    Article  MathSciNet  MATH  Google Scholar 

  26. Wang GG, Deb S, Cui Z (2015) Monarch butterfly optimization. Neural Comput Appl. doi:10.1007/s00521-015-1923-y

    Google Scholar 

  27. Li X, Wang J, Yin M (2014) Enhancing the performance of cuckoo search algorithm using orthogonal learning method. Neural Comput Appl 24(6):1233–1247

    Article  Google Scholar 

  28. Li X, Zhang J, Yin M (2014) Animal migration optimization: an optimization algorithm inspired by animal migration behavior. Neural Comput Appl 24(7–8):1867–1877

    Article  Google Scholar 

  29. Zhou S, Chen H, Xu R, Li X (2014) Minimising makespan on a single batch processing machine with dynamic job arrivals and non-identical job sizes. Int J Prod Res 52(8):2258–2274

    Article  Google Scholar 

  30. Venugopal D, Sarkhel S, Gogate V (2015) Just count the satisfied groundings: scalable local-search and sampling based inference in MLNs. In: Twenty-ninth AAAI conference on artificial intelligence

  31. Burke EK, Hyde MR, Kendall G (2012) Grammatical evolution of local search heuristics. IEEE Trans Evolut Comput 16(3):406–417

    Article  Google Scholar 

  32. Pan QK, Ruiz R (2012) Local search methods for the flowshop scheduling problem with flowtime minimization. Eur J Oper Res 222(1):31–43

    Article  MathSciNet  MATH  Google Scholar 

  33. Ke L, Zhang Q, Battiti R (2014) Hybridization of decomposition and local search for multiobjective optimization. IEEE T Cybern 44(10):1808–1820

    Article  Google Scholar 

  34. Croes GA (1958) A method for solving traveling-salesman problems. Oper Res 6(6):791–812

    Article  MathSciNet  Google Scholar 

  35. González MA, Vela CR, Varela R (2015) Scatter search with path relinking for the flexible job shop scheduling problem. Eur J Oper Res 245(1):35–45

    Article  MathSciNet  MATH  Google Scholar 

  36. Tarantilis CD, Anagnostopoulou AK, Repoussis PP (2013) Adaptive path relinking for vehicle routing and scheduling problems with product returns. Transp Sci 47(3):356–379

    Article  Google Scholar 

  37. Lacomme P, Prins C, Prodhon C, Ren L (2015) A multi-start split based path relinking (MSSPR) approach for the vehicle routing problem with route balancing. Eng Appl Artif Intel 38:237–251

    Article  Google Scholar 

  38. Wang Y, Lü Z, Glover F, Hao JK (2012) Path relinking for unconstrained binary quadratic programming. Eur J Oper Res 223(3):595–604

    Article  MathSciNet  MATH  Google Scholar 

  39. Duarte A, Sánchez-Oro J, Resende MG, Glover F, Martí R (2015) Greedy randomized adaptive search procedure with exterior path relinking for differential dispersion minimization. Inform Sci 296:46–60

    Article  MathSciNet  Google Scholar 

  40. Glover F (1997) Tabu search and adaptive memory programming—advances, applications and challenges. Interfaces Comput Sci Oper Research. Springer, New York, pp 1–75

    Google Scholar 

  41. Glover F, Laguna M, Martí R (2000) Fundamentals of scatter search and path relinking. Control Cybern 29(3):653–684

    MathSciNet  MATH  Google Scholar 

  42. Resende MG, Ribeiro CC (2003) A GRASP with path-relinking for private virtual circuit routing. Networks 41(2):104–114

    Article  MathSciNet  MATH  Google Scholar 

  43. Aiex RM, Resende MG, Pardalos PM, Toraldo G (2005) GRASP with path relinking for three-index assignment. Inform J Comput 17(2):224–247

    Article  MathSciNet  MATH  Google Scholar 

  44. Ribeiro CC, Rosseti I (2002) A parallel GRASP heuristic for the 2-path network design problem. Euro-par 2002 parallel processing. Springer, Berlin, pp 922–926

    Chapter  Google Scholar 

  45. Ribeiro CC, Uchoa E, Werneck RF (2002) A hybrid GRASP with perturbations for the Steiner problem in graphs. Inform J Comput 14(3):228–246

    Article  MathSciNet  MATH  Google Scholar 

  46. Aiex RM, Binato S, Resende MG (2003) Parallel GRASP with path-relinking for job shop scheduling. Parallel Comput 29(4):393–430

    Article  MathSciNet  Google Scholar 

  47. Wang Y, Yin M, Ouyang D et al (2016) A novel local search algorithm with configuration checking and scoring mechanism for the set k-covering problem. Int Trans Oper Res. doi:10.1111/itor.12280

    Google Scholar 

  48. Wang Y, Ouyang DT, Zhang L et al (2015) A novel local search for unicost set covering problem using hyperedge configuration checking and weight diversity. Sci China Inf Sci. doi:10.1007/s11432-015-5377-8

    Google Scholar 

  49. Wang Y, Li R, Zhou Y et al (2016) A path cost-based GRASP for minimum independent dominating set problem. Neural Comput Appl. doi:10.1007/s00521-016-2324-6

    Google Scholar 

  50. Li R, Hu S, Wang Y, Yin M (2016) A local search algorithm with tabu strategy and perturbation mechanism for generalized vertex cover problem. Neural Comput Appl. doi:10.1007/s00521-015-2172-9

    Google Scholar 

  51. Wang GG, Guo L, Gandomi AH et al (2014) Chaotic krill herd algorithm. Inf Sci 274:17–34

    Article  MathSciNet  Google Scholar 

  52. Wang G, Guo L, Wang H et al (2014) Incorporating mutation scheme into krill herd algorithm for global numerical optimization. Neural Comput Appl 24(3–4):853–871

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported in part by National Natural Science Foundation of China (NSFC) under Grant Nos. (61370156, 61403076, 61403077) and Program for New Century Excellent Talents in University (NCET-13-0724).

Author information

Authors and Affiliations

  1. School of Computer Science and Information Technology, Northeast Normal University, Changchun, Jilin Province, 130117, People’s Republic of China

    Xin Zhang, Xiangtao Li & Jianan Wang

Authors
  1. Xin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiangtao Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jianan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jianan Wang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, X., Li, X. & Wang, J. Local search algorithm with path relinking for single batch-processing machine scheduling problem. Neural Comput & Applic 28 (Suppl 1), 313–326 (2017). https://doi.org/10.1007/s00521-016-2339-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00521-016-2339-z

Keywords

Search

Navigation