An evolutionary algorithm based hyper-heuristic for the set packing problem

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

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

Abstract

Utilizing knowledge of the problem of interest and lessons learned from solving similar problems would help to find the final optimal solution of better quality. A hyper-heuristic algorithm is to gain an advantage of such process. In this paper, we present an evolutionary algorithm based hyper-heuristic framework for solving the set packing problem (SPP). The SPP is a typical NP-hard problem. The hyper-heuristic is comprising of high level and low level. The higher level is mainly engaged in generating or constructing a heuristic. An evolutionary algorithm with guided mutation (EA/G) is employed at the high level. Whereas a set of problem-independent and problem-specific heuristics, called low level heuristics, are employed at the low level of hyper-heuristic. EA/G is recently added to the class of the evolutionary algorithms that try to utilize the complementary characteristics of genetic algorithms (GAs) and estimation of distribution algorithms (EDAs) to generate new offspring. In EA/G, the guided mutation operator generates an offspring by sampling the probability vector. The proposed approach is compared with the state-of-the-art approaches reported in the literature. The computational results show the effectiveness of the proposed 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
Pages259-268
Number of pages10
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
Heuristic algorithms
Mathematical operators
Computational complexity
Genetic algorithms
Sampling

Keywords

  • Constrained optimization
  • Estimation of distribution algorithm
  • Genetic algorithm
  • Guided mutation
  • Heuristic
  • Hyper-heuristic
  • Set packing problem

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Chaurasia, S. N., Jung, D., Lee, H. M., & Kim, J. H. (2019). An evolutionary algorithm based hyper-heuristic for the set packing problem. 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. 259-268). (Advances in Intelligent Systems and Computing; Vol. 741). Springer Verlag. https://doi.org/10.1007/978-981-13-0761-4_26

An evolutionary algorithm based hyper-heuristic for the set packing problem. / Chaurasia, Sachchida Nand; 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. 259-268 (Advances in Intelligent Systems and Computing; Vol. 741).

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

Chaurasia, SN, Jung, D, Lee, HM & Kim, JH 2019, An evolutionary algorithm based hyper-heuristic for the set packing problem. 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. 259-268, 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_26
Chaurasia SN, Jung D, Lee HM, Kim JH. An evolutionary algorithm based hyper-heuristic for the set packing problem. 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. 259-268. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-981-13-0761-4_26
Chaurasia, Sachchida Nand ; Jung, Donghwi ; Lee, Ho Min ; Kim, Joong Hoon. / An evolutionary algorithm based hyper-heuristic for the set packing problem. 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. 259-268 (Advances in Intelligent Systems and Computing).
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