Spherical Local Search for Global Optimization

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Abstract

This paper proposed spherical local search (SLS) for solving unconstrained optimization problems in three dimensions. The algorithm begins with a randomly chosen point in the search domain. Then, spherical trust region around this point is defined by the radius of SLS; where any point in this region is feasible. Finally, SLS can move from current search point to obtain a new best point by using three strategies of search: radius, azimuth, and inclination. These strategies are modified during the search process. SLS is tested on the set of the CEC’2005 special session on real parameter optimization. Results show the robustness and effectiveness of the proposed method.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018
EditorsAhmad Taher Azar, Aboul Ella Hassanien, Khaled Shaalan, Mohamed F. Tolba
PublisherSpringer Verlag
Pages304-312
Number of pages9
ISBN (Print)9783319990095
DOIs
StatePublished - 2019
Event4th International Conference on Advanced Intelligent Systems and Informatics, AISI 2018 - Cairo, Egypt
Duration: 3 Sep 20185 Sep 2018

Publication series

NameAdvances in Intelligent Systems and Computing
Volume845
ISSN (Print)2194-5357

Conference

Conference4th International Conference on Advanced Intelligent Systems and Informatics, AISI 2018
Country/TerritoryEgypt
CityCairo
Period3/09/185/09/18

Keywords

  • Global optimization
  • Local search
  • Optimization
  • Spherical local search
  • Unconstrained optimization

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