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Development of Novel Hybrid Multi-Verse Optimizer with Sine Cosine Algorithm for Better Global Optimization

Pham Vu Hong Son

https://orcid.org/0000-0002-9788-0627

Ho Chi Minh City University of Technology (HCMUT), Vietnam National University (VNU-HCM), Ho Chi Minh City, Vietnam

E-mail Address: pvhson@hcmut.edu.vn

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and

Nguyen Dang Nghiep Trinh

https://orcid.org/0000-0002-8299-1244

Ho Chi Minh City University of Technology (HCMUT), Vietnam National University (VNU-HCM), Ho Chi Minh City, Vietnam

E-mail Address: ndntrinh.sdh20@hcmut.edu.vn

Corresponding author.

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https://doi.org/10.1142/S1469026824500020Cited by:2 (Source: Crossref)

Abstract

The sine cosine algorithm (SCA) and multi-verse optimizer (MVO) are the recognized optimization strategies frequently employed in numerous scientific areas. However, both SCA and MVO grapple with optimizing the transition between the exploitation and exploration mechanisms. Furthermore, MVO exhibits constraints in its exploitation capabilities. To tackle these limitations, this paper introduces a hybrid model termed SMVO, combining the advantages of both SCA and MVO. This hybrid approach seeks to harmonize exploitation and exploration stages by leveraging the unique advantages of each parent algorithm. The efficacy of SMVO was assessed using 23 benchmark test functions, revealing its competitive performance against not only SCA and MVO but also the ant lion optimization (ALO) and the dragonfly algorithm (DA). Additionally, SMVO’s applicability was further validated by successfully addressing three distinct engineering optimization challenges, underscoring its stability and promise as a global optimization tool.

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