An evolutionary algorithm based hyper-heuristic for the job-shop scheduling problem with no-wait constraint

Sachchida Nand Chaurasia, Shyam Sundar, Donghwi Jung, Ho Min Lee, Joong Hoon Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, we developed an evolutionary algorithm with guided mutation (EA/G) based hyper-heuristic for solving the job-shop scheduling problem with no-wait constraint (JSPNW). The 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. This problem is a typical NP-hard problem. The hyper-heuristic algorithm comprises of two level frameworks. In the high-level, an evolutionary algorithm is employed to explore the search space. The low-level, which is comprised of generic as well as problem-specific heuristics such as guided mutation, multi-insert points and multi-swap. EA/G is a recent addition to the class of evolutionary algorithm that can be considered as a hybridization of genetic algorithms (GAs) and estimation of distribution algorithms (EDAs), and which tries to overcome the shortcomings of both. In GAs, the location information of the solutions found so far is directly used to generate offspring. On the other hand, EDAs use global statistical information to generate new offspring. In EDAs the global statistical information is stored in the form probability vector, and a new offspring is generated by sampling this probability vector. We have compared our approach with the state-of-the-art approaches. The computational results show the effectiveness of our approach.

Original languageEnglish
Title of host publicationHarmony Search and Nature Inspired Optimization Algorithms - Theory and Applications, ICHSA 2018
EditorsJagdish Chand Bansal, Joong Hoon Kim, Anupam Yadav, Kusum Deep, Neha Yadav
PublisherSpringer Verlag
Pages249-257
Number of pages9
ISBN (Print)9789811307607
DOIs
Publication statusPublished - 2019 Jan 1
Event4th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2018 - Gurgaon, India
Duration: 2018 Feb 72018 Feb 9

Publication series

NameAdvances in Intelligent Systems and Computing
Volume741
ISSN (Print)2194-5357

Conference

Conference4th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2018
CountryIndia
CityGurgaon
Period18/2/718/2/9

Fingerprint

Evolutionary algorithms
Genetic algorithms
Heuristic algorithms
Computational complexity
Sampling
Job shop scheduling

Keywords

  • Constrained optimization
  • Estimation of distribution algorithms
  • Genetic algorithms
  • Guided mutation
  • Heuristic
  • Hyper-heuristic
  • Job-shop
  • No-wait
  • Scheduling

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Chaurasia, S. N., Sundar, S., Jung, D., Lee, H. M., & Kim, J. H. (2019). An evolutionary algorithm based hyper-heuristic for the job-shop scheduling problem with no-wait constraint. In J. C. Bansal, J. H. Kim, A. Yadav, K. Deep, & N. Yadav (Eds.), Harmony Search and Nature Inspired Optimization Algorithms - Theory and Applications, ICHSA 2018 (pp. 249-257). (Advances in Intelligent Systems and Computing; Vol. 741). Springer Verlag. https://doi.org/10.1007/978-981-13-0761-4_25

An evolutionary algorithm based hyper-heuristic for the job-shop scheduling problem with no-wait constraint. / Chaurasia, Sachchida Nand; Sundar, Shyam; Jung, Donghwi; Lee, Ho Min; Kim, Joong Hoon.

Harmony Search and Nature Inspired Optimization Algorithms - Theory and Applications, ICHSA 2018. ed. / Jagdish Chand Bansal; Joong Hoon Kim; Anupam Yadav; Kusum Deep; Neha Yadav. Springer Verlag, 2019. p. 249-257 (Advances in Intelligent Systems and Computing; Vol. 741).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chaurasia, SN, Sundar, S, Jung, D, Lee, HM & Kim, JH 2019, An evolutionary algorithm based hyper-heuristic for the job-shop scheduling problem with no-wait constraint. in JC Bansal, JH Kim, A Yadav, K Deep & N Yadav (eds), Harmony Search and Nature Inspired Optimization Algorithms - Theory and Applications, ICHSA 2018. Advances in Intelligent Systems and Computing, vol. 741, Springer Verlag, pp. 249-257, 4th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2018, Gurgaon, India, 18/2/7. https://doi.org/10.1007/978-981-13-0761-4_25
Chaurasia SN, Sundar S, Jung D, Lee HM, Kim JH. An evolutionary algorithm based hyper-heuristic for the job-shop scheduling problem with no-wait constraint. In Bansal JC, Kim JH, Yadav A, Deep K, Yadav N, editors, Harmony Search and Nature Inspired Optimization Algorithms - Theory and Applications, ICHSA 2018. Springer Verlag. 2019. p. 249-257. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-981-13-0761-4_25
Chaurasia, Sachchida Nand ; Sundar, Shyam ; Jung, Donghwi ; Lee, Ho Min ; Kim, Joong Hoon. / An evolutionary algorithm based hyper-heuristic for the job-shop scheduling problem with no-wait constraint. Harmony Search and Nature Inspired Optimization Algorithms - Theory and Applications, ICHSA 2018. editor / Jagdish Chand Bansal ; Joong Hoon Kim ; Anupam Yadav ; Kusum Deep ; Neha Yadav. Springer Verlag, 2019. pp. 249-257 (Advances in Intelligent Systems and Computing).
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