KU battle of metaheuristic optimization algorithms 2: Performance test

Joong Hoon Kim, Young Hwan Choi, Thi Thuy Ngo, Jiho Choi, Ho Min Lee, Yeon Moon Choo, Eui Hoon Lee, Do Guen Yoo, Ali Sadollah, Donghwi Jung

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

1 Citation (Scopus)

Abstract

In the previous companion paper, six new/improved metaheuristic optimization algorithms developed by members of Hydrosystem laboratory in Korea University (KU) are introduced. The six algorithms are Cancer Treatment Algorithm (CTA), Extraordinary Particle Swarm Optimization (EPSO), Improved Cluster HS (ICHS), Multi-Layered HS (MLHS), Sheep Shepherding Algorithm (SSA), and Vision Correction Algorithm (VCA). The six algorithms are tested and compared through six well-known unconstrained benchmark functions and a pipe sizing problem of water distribution network. Performance measures such as mean, best, and worst solutions (under given maximum number of function evaluations) are used for the comparison. Optimization results are obtained from thirty independent optimization trials. Obtained Results show that some of the newly developed/improved algorithms show superior performance with respect to mean, best, and worst solutions when compared to other existing algorithms.

Original languageEnglish
Title of host publicationAdvances in Intelligent Systems and Computing
PublisherSpringer Verlag
Pages207-213
Number of pages7
Volume382
ISBN (Print)9783662479254
DOIs
Publication statusPublished - 2016
Event2nd International Conference on Harmony Search Algorithm, ICHSA 2015 - Seoul, Korea, Republic of
Duration: 2015 Aug 192015 Aug 21

Publication series

NameAdvances in Intelligent Systems and Computing
Volume382
ISSN (Print)21945357

Other

Other2nd International Conference on Harmony Search Algorithm, ICHSA 2015
CountryKorea, Republic of
CitySeoul
Period15/8/1915/8/21

Keywords

  • Cancer treatment algorithm
  • Extraordinary particle swarm optimization
  • Improved cluster HS
  • Multi-Layered HS
  • Sheep shepherding algorithm
  • Vision correction algorithm

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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  • Cite this

    Kim, J. H., Choi, Y. H., Ngo, T. T., Choi, J., Lee, H. M., Choo, Y. M., Lee, E. H., Yoo, D. G., Sadollah, A., & Jung, D. (2016). KU battle of metaheuristic optimization algorithms 2: Performance test. In Advances in Intelligent Systems and Computing (Vol. 382, pp. 207-213). (Advances in Intelligent Systems and Computing; Vol. 382). Springer Verlag. https://doi.org/10.1007/978-3-662-47926-1_20