Chaotic Stochastic Paint Optimizer (CSPO)

Nima Khodadadi, Seyed Mohammad Mirjalili, Seyedeh Zahra Mirjalili, Seyedali Mirjalili

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Optimization of engineering problems requires addressing several common difficulties in the optimization problem, including but not limited to a large number of decision variables, multiple often conflicting objectives, constraints, locally optimal solutions, and expensive objective functions. It is pretty common that an algorithm performs very well on test functions but struggles when applying to real-world problems. This paper proposes a chaotic version of the recently proposed algorithm called chaotic stochastic paint optimizer (CSPO). A comparative study with other meta-heuristics demonstrates the merits of this algorithm and the change applied in this work.

Original languageEnglish
Title of host publicationLecture Notes on Data Engineering and Communications Technologies
PublisherSpringer Science and Business Media Deutschland GmbH
Pages195-205
Number of pages11
DOIs
Publication statusPublished - 2022

Publication series

NameLecture Notes on Data Engineering and Communications Technologies
Volume140
ISSN (Print)2367-4512
ISSN (Electronic)2367-4520

Keywords

  • Chaotic stochastic paint optimizer
  • Engineering problems
  • Optimization
  • Stochastic paint optimizer

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