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

1 Citation (Scopus)


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
Number of pages10
ISBN (Print)9789811307607
Publication statusPublished - 2019
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
ISSN (Print)2194-5357


Conference4th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2018


  • 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)


Dive into the research topics of 'An evolutionary algorithm based hyper-heuristic for the set packing problem'. Together they form a unique fingerprint.

Cite this