Differential Vectors Empower Snow Ablation Optimizer

Tianfang Lu*, Haotian Li, Yifei Yang, Zhiwei Yu, Zhenyu Lei, Shangce Gao*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

The Snow Ablation Optimizer (SAO) algorithm represents a new intelligent search method founded on the sublimation and melting phenomena of snow. It incorporates a dual-population mechanism to balance exploration and exploitation. However, one limitation of SAO is its propensity to become trapped in local optima. Coincidentally, the Differential Evolution (DE) algorithm exhibits strong global search capabilities. In light of this, we propose a fusion algorithm, named DESAO, that combines the strengths of SAO and DE. Our experimental results, conducted on the IEEE CEC2017 benchmark, demonstrate DESAO's superiority of optimization capabilities and rapid convergence rates.

Original languageEnglish
Title of host publicationIEEE ITAIC 2023 - IEEE 11th Joint International Information Technology and Artificial Intelligence Conference
EditorsBing Xu, Kefen Mou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1382-1386
Number of pages5
ISBN (Electronic)9798350333664
DOIs
StatePublished - 2023
Event11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023 - Chongqing, China
Duration: 2023/12/082023/12/10

Publication series

NameIEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)
ISSN (Print)2693-2865

Conference

Conference11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023
Country/TerritoryChina
CityChongqing
Period2023/12/082023/12/10

Keywords

  • Computation Intelligence
  • Differential Evolution
  • Meta-heuristic Algorithms
  • Snow Ablation Optimizer

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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