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Evolutionary Computation for Multicomponent Problems: Opportunities and Future Directions

  • Mohammad Reza Bonyadi
  • , Zbigniew Michalewicz
  • , Markus Wagner
  • , Frank Neumann

Research output: Chapter in Book/Report/Conference proceedingChapter (Book)Researchpeer-review

Abstract

Over the past 30 years, many researchers in the field of evolutionary computation have put a lot of effort to introduce various approaches for solving hard problems. Most of these problems have been inspired by major industries so that solving them, by providing either optimal or near optimal solution, was of major significance. Indeed, this was a very promising trajectory as advances in these problem-solving approaches could result in adding values to major industries. In this chapter, we revisit this trajectory to find out whether the attempts that started three decades ago are still aligned with the same goal, as complexities of real-world problems increased significantly. We present some examples of modern real-world problems, discuss why they might be difficult to solve, and whether there is any mismatch between these examples and the problems that are investigated in the evolutionary computation area.

Original languageEnglish
Title of host publicationOptimization in Industry
Subtitle of host publicationPresent Practices and Future Scopes
EditorsShubhabrata Datta, J. Paulo Davim
Place of PublicationCham Switzerland
PublisherSpringer
Chapter2nd
Pages13-30
Number of pages18
Edition1st
ISBN (Electronic)9783030016418
ISBN (Print)9783030016401
DOIs
Publication statusPublished - 2019
Externally publishedYes

Publication series

NameManagement and Industrial Engineering
PublisherSpringer
ISSN (Print)2365-0532
ISSN (Electronic)2365-0540

Keywords

  • Cooperative coevolution
  • Evolutionary algorithms
  • Multicomponent optimization
  • Traveling thief problem

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