Iterated Greedy Algorithms for Combinatorial Optimization: A Systematic Literature Review

Research output: Chapter in Book/Report/Conference proceedingsChapterpeer-review

Abstract

Metaheuristics are essential tools for efficiently solving combinatorial optimization problems in arising from many fields. As incomplete methods, metaheuristics can provide goodquality results in a very short time. Among these approaches, the Iterated Greedy algorithm (IG) has appeared as a powerful and flexible method for finding near-optimal solutions to combinatorial problems. In this paper, we conducted a comprehensive systematic literature review on the variants of IG approach, and its applications covering the period from its inception in 2007 up to 2022. To the best of our knowledge, this is the first work in which all operators and aspects of IG are discussed to provide a detailed idea about this approach.

Original languageEnglish
Title of host publication2023 20th ACS/IEEE International Conference on Computer Systems and Applications, AICCSA 2023 - Proceedings
PublisherIEEE Computer Society
ISBN (Electronic)9798350319439
DOIs
Publication statusPublished - 2023
Event20th ACS/IEEE International Conference on Computer Systems and Applications, AICCSA 2023 - Giza, Egypt
Duration: 4 Dec 20237 Dec 2023

Publication series

NameProceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA
ISSN (Print)2161-5322
ISSN (Electronic)2161-5330

Conference

Conference20th ACS/IEEE International Conference on Computer Systems and Applications, AICCSA 2023
Country/TerritoryEgypt
CityGiza
Period4/12/237/12/23

Keywords

  • Destruction-reconstruction
  • Iterated Greedy
  • Meta-heuristics
  • Optimization
  • Systematic Literature

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