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Enhanced Remora Optimization Algorithm for Solving Constrained Engineering Optimization Problems

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Bibliographic Details
Title: Enhanced Remora Optimization Algorithm for Solving Constrained Engineering Optimization Problems
Authors: Shuang Wang, Abdelazim G. Hussien, Heming Jia, Laith Abualigah, Rong Zheng
Source: Mathematics ; Volume 10 ; Issue 10 ; Pages: 1696
Publisher Information: Multidisciplinary Digital Publishing Institute
Publication Year: 2022
Collection: MDPI Open Access Publishing
Subject Terms: remora optimization algorithm, adaptive dynamic probability, restart strategy, metaheuristic algorithm, constrained engineering problems
Description: Remora Optimization Algorithm (ROA) is a recent population-based algorithm that mimics the intelligent traveler behavior of Remora. However, the performance of ROA is barely satisfactory; it may be stuck in local optimal regions or has a slow convergence, especially in high dimensional complicated problems. To overcome these limitations, this paper develops an improved version of ROA called Enhanced ROA (EROA) using three different techniques: adaptive dynamic probability, SFO with Levy flight, and restart strategy. The performance of EROA is tested using two different benchmarks and seven real-world engineering problems. The statistical analysis and experimental results show the efficiency of EROA.
Document Type: text
File Description: application/pdf
Language: English
Relation: E: Applied Mathematics; https://dx.doi.org/10.3390/math10101696
DOI: 10.3390/math10101696
Availability: https://doi.org/10.3390/math10101696
Rights: https://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.D90B2D07
Database: BASE
Description
Abstract:Remora Optimization Algorithm (ROA) is a recent population-based algorithm that mimics the intelligent traveler behavior of Remora. However, the performance of ROA is barely satisfactory; it may be stuck in local optimal regions or has a slow convergence, especially in high dimensional complicated problems. To overcome these limitations, this paper develops an improved version of ROA called Enhanced ROA (EROA) using three different techniques: adaptive dynamic probability, SFO with Levy flight, and restart strategy. The performance of EROA is tested using two different benchmarks and seven real-world engineering problems. The statistical analysis and experimental results show the efficiency of EROA.
DOI:10.3390/math10101696