Optimal Peaks Detected-Based Differential Evolution for Multimodal Optimization Problems

Si Jia JIE, Yi JIANG*, Xin-Xin XU, Sam KWONG, Jun ZHANG, Zhi-Hui ZHAN*

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review


Multimodal optimization problems (MMOPs) have multiple global optima, hence the algorithm must preserve population diversity to locate multiple global optima and ensure the precision of the obtained solutions simultaneously. To achieve these, the niching technique is widely applied. Although the niching technique shows encouraging performance, some niches may continuously evolve even though accurate enough global optima in their regions have been found. This may cause the waste of computational resources and the inefficiency of search behavior. To maintain population diversity and accuracy, and to break through the mentioned deficiency, an optimal peaks detected-based differential evolution (OPPDE) algorithm is proposed, which has three novel components. Firstly, to maintain population diversity, OPDDE designs a parameter-insensitive OPTICS-based niching strategy to automatically partition niches. Secondly, to avoid wasting computation resources on founded global optima and enhance search efficiency, OPDDE designs an optimal peaks detection strategy that uses historical information to identify the founded global optima. Thirdly, a dynamic step local search strategy is used to refine solutions. The proposed OPDDE algorithm generally superiors some state-of-the-art algorithms regarding both the accuracy and completeness of solutions, according to experiments on widely used MMOP benchmarks.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Systems, Man, and Cybernetics: Improving the Quality of Life, SMC 2023, Proceedings
Number of pages6
ISBN (Electronic)9798350337020
ISBN (Print)9798350337037
Publication statusPublished - 2023
Externally publishedYes
Event2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023 - Hybrid, Honolulu, United States
Duration: 1 Oct 20234 Oct 2023

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN (Print)1062-922X


Conference2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023
Country/TerritoryUnited States
CityHybrid, Honolulu

Bibliographical note

Publisher Copyright:
© 2023 IEEE.


  • differential evolution
  • dynamic step local search
  • evolutionary computation
  • multimodal optimization problems (MMOPs)
  • OPTICS-based niching
  • optimal peaks detection


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