Coati Optimization Algorithm: A new bio-inspired metaheuristic algorithm for solving optimization problems

Knowledge-Based Systems, Journal Year: 2022, Volume and Issue: 259, P. 110011 - 110011

Published: Oct. 28, 2022

In this paper, a new metaheuristic algorithm called the Coati Optimization Algorithm (COA) is introduced, which mimics coati behavior in nature. The fundamental idea of COA simulation two natural behaviors coatis: (i) their when attacking and hunting iguanas (ii) escape from predators. implementation steps are described mathematically modeled phases exploration exploitation. performance evaluated on fifty-one objective functions, including twenty-nine functions IEEE CEC-2017 test suite twenty-two real-world applications CEC-2011 suite. COA's results compared to those eleven well-known algorithms. indicate that has an evident superiority over algorithms by balancing global search exploitation local search, far more competitive. To assess effectiveness applications, proposed approach implemented four practical optimization problems, high capability dealing with these types problems.

Language: Английский

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Artificial rabbits optimization: A new bio-inspired meta-heuristic algorithm for solving engineering optimization problems

Engineering Applications of Artificial Intelligence, Journal Year: 2022, Volume and Issue: 114, P. 105082 - 105082

Published: July 11, 2022

Language: Английский

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An Overview of Variants and Advancements of PSO Algorithm

Applied Sciences, Journal Year: 2022, Volume and Issue: 12(17), P. 8392 - 8392

Published: Aug. 23, 2022

Particle swarm optimization (PSO) is one of the most famous swarm-based techniques inspired by nature. Due to its properties flexibility and easy implementation, there an enormous increase in popularity this nature-inspired technique. has gained prompt attention from every field researchers. Since origin 1995 till now, researchers have improved original varying ways. They derived new versions it, such as published theoretical studies on various parameters PSO, proposed many variants algorithm numerous other advances. In present paper, overview PSO presented. On hand, basic concepts are explained, advances relation including modifications, extensions, hybridization, analysis, included.

Language: Английский

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Gazelle optimization algorithm: a novel nature-inspired metaheuristic optimizer

Neural Computing and Applications, Journal Year: 2022, Volume and Issue: 35(5), P. 4099 - 4131

Published: Oct. 20, 2022

Language: Английский

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Kepler optimization algorithm: A new metaheuristic algorithm inspired by Kepler’s laws of planetary motion

Knowledge-Based Systems, Journal Year: 2023, Volume and Issue: 268, P. 110454 - 110454

Published: March 11, 2023

Language: Английский

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Zebra Optimization Algorithm: A New Bio-Inspired Optimization Algorithm for Solving Optimization Algorithm

IEEE Access, Journal Year: 2022, Volume and Issue: 10, P. 49445 - 49473

Published: Jan. 1, 2022

In this paper, a new bio-inspired metaheuristic algorithm called Zebra Optimization Algorithm (ZOA) is developed; its fundamental inspiration the behavior of zebras in nature. ZOA simulates foraging and their defense strategy against predators' attacks. The steps are described then mathematically modeled. performance optimization evaluated on sixty-eight benchmark functions, including unimodal, high-dimensional multimodal, fixed-dimensional CEC2015, CEC2017. results obtained from compared with nine well-known algorithms. simulation show that can solve problems by creating suitable balance between exploration exploitation has superior to competitor ZOA's ability real-world been tested four engineering design problems, namely, tension/compression spring, welded beam, speed reducer, pressure vessel. an effective optimizer determining values variables these

Language: Английский

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Nutcracker optimizer: A novel nature-inspired metaheuristic algorithm for global optimization and engineering design problems

Knowledge-Based Systems, Journal Year: 2023, Volume and Issue: 262, P. 110248 - 110248

Published: Jan. 3, 2023

Language: Английский

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Starling murmuration optimizer: A novel bio-inspired algorithm for global and engineering optimization

Computer Methods in Applied Mechanics and Engineering, Journal Year: 2022, Volume and Issue: 392, P. 114616 - 114616

Published: Feb. 12, 2022

Language: Английский

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Greylag Goose Optimization: Nature-inspired optimization algorithm

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 238, P. 122147 - 122147

Published: Oct. 18, 2023

Language: Английский

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Hippopotamus optimization algorithm: a novel nature-inspired optimization algorithm

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Feb. 29, 2024

Abstract The novelty of this article lies in introducing a novel stochastic technique named the Hippopotamus Optimization (HO) algorithm. HO is conceived by drawing inspiration from inherent behaviors observed hippopotamuses, showcasing an innovative approach metaheuristic methodology. conceptually defined using trinary-phase model that incorporates their position updating rivers or ponds, defensive strategies against predators, and evasion methods, which are mathematically formulated. It attained top rank 115 out 161 benchmark functions finding optimal value, encompassing unimodal high-dimensional multimodal functions, fixed-dimensional as well CEC 2019 test suite 2014 dimensions 10, 30, 50, 100 Zigzag Pattern suggests demonstrates noteworthy proficiency both exploitation exploration. Moreover, it effectively balances exploration exploitation, supporting search process. In light results addressing four distinct engineering design challenges, has achieved most efficient resolution while concurrently upholding adherence to designated constraints. performance evaluation algorithm encompasses various aspects, including comparison with WOA, GWO, SSA, PSO, SCA, FA, GOA, TLBO, MFO, IWO recognized extensively researched metaheuristics, AOA recently developed algorithms, CMA-ES high-performance optimizers acknowledged for success IEEE competition. According statistical post hoc analysis, determined be significantly superior investigated algorithms. source codes publicly available at https://www.mathworks.com/matlabcentral/fileexchange/160088-hippopotamus-optimization-algorithm-ho .

Language: Английский

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