A hybrid algorithm of grey wolf optimizer and harris hawks optimization for solving global optimization problems with improved convergence performance DOI Creative Commons
Binbin Tu, Fei Wang,

Yan Huo

et al.

Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: Dec. 21, 2023

The grey wolf optimizer is an effective and well-known meta-heuristic algorithm, but it also has the weaknesses of insufficient population diversity, falling into local optimal solutions easily, unsatisfactory convergence speed. Therefore, we propose a hybrid (HGWO), based mainly on exploitation phase harris hawk optimization. It includes initialization with Latin hypercube sampling, nonlinear factor perturbations, some extended exploration strategies. In HGWO, wolves can have hawks-like flight capabilities during position updates, which greatly expands search range improves global searchability. By incorporating greedy will relocate only if new location superior to current one. This paper assesses performance (HGWO) by comparing other heuristic algorithms enhanced schemes optimizer. evaluation conducted using 23 classical benchmark test functions CEC2020. experimental results reveal that HGWO algorithm performs well in terms its ability, speed, accuracy. Additionally, demonstrates considerable advantages solving engineering problems, thus substantiating effectiveness applicability.

Language: Английский

Zebra Optimization Algorithm: A New Bio-Inspired Optimization Algorithm for Solving Optimization Algorithm DOI Creative Commons
Eva Trojovská, Mohammad Dehghani, Pavel Trojovský

et al.

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

Citations

236
Advances in Sparrow Search Algorithm: A Comprehensive Survey DOI Open Access
Farhad Soleimanian Gharehchopogh,

Mohammad Namazi,

Laya Ebrahimi

et al.

Archives of Computational Methods in Engineering, Journal Year: 2022, Volume and Issue: 30(1), P. 427 - 455

Published: Aug. 22, 2022

Language: Английский

Citations

224
Quantum-inspired metaheuristic algorithms: comprehensive survey and classification DOI
Farhad Soleimanian Gharehchopogh

Artificial Intelligence Review, Journal Year: 2022, Volume and Issue: 56(6), P. 5479 - 5543

Published: Nov. 2, 2022

Language: Английский

Citations

134
A Systematic Review of the Whale Optimization Algorithm: Theoretical Foundation, Improvements, and Hybridizations DOI Open Access
Mohammad H. Nadimi-Shahraki, Hoda Zamani, Zahra Asghari Varzaneh

et al.

Archives of Computational Methods in Engineering, Journal Year: 2023, Volume and Issue: 30(7), P. 4113 - 4159

Published: May 27, 2023

Language: Английский

Citations

121
Slime Mould Algorithm: A Comprehensive Survey of Its Variants and Applications DOI Open Access
Farhad Soleimanian Gharehchopogh, Alaettin Uçan, Turgay İbrikçi

et al.

Archives of Computational Methods in Engineering, Journal Year: 2023, Volume and Issue: 30(4), P. 2683 - 2723

Published: Jan. 12, 2023

Language: Английский

Citations

109
An improved African vultures optimization algorithm using different fitness functions for multi-level thresholding image segmentation DOI
Farhad Soleimanian Gharehchopogh, Turgay İbrikçi

Multimedia Tools and Applications, Journal Year: 2023, Volume and Issue: 83(6), P. 16929 - 16975

Published: July 19, 2023

Language: Английский

Citations

101
DMDE: Diversity-maintained multi-trial vector differential evolution algorithm for non-decomposition large-scale global optimization DOI
Mohammad H. Nadimi-Shahraki, Hoda Zamani

Expert Systems with Applications, Journal Year: 2022, Volume and Issue: 198, P. 116895 - 116895

Published: March 17, 2022

Language: Английский

Citations

94
Waterwheel Plant Algorithm: A Novel Metaheuristic Optimization Method DOI Open Access
Abdelaziz A. Abdelhamid,

S. K. Towfek,

Nima Khodadadi

et al.

Processes, Journal Year: 2023, Volume and Issue: 11(5), P. 1502 - 1502

Published: May 15, 2023

Attempting to address optimization problems in various scientific disciplines is a fundamental and significant difficulty requiring optimization. This study presents the waterwheel plant technique (WWPA), novel stochastic motivated by natural systems. The proposed WWPA’s basic concept based on modeling plant’s behavior while hunting expedition. To find prey, WWPA uses plants as search agents. We present mathematical model for use addressing problems. Twenty-three objective functions of varying unimodal multimodal types were used assess performance. results optimizing demonstrate strong exploitation ability get close optimal solution, show exploration zero major region space. Three engineering design also gauge potential improving practical programs. effectiveness was evaluated comparing its with those seven widely metaheuristic algorithms. When compared eight competing algorithms, simulation analyses that outperformed them finding more proportionate balance between exploitation.

Language: Английский

Citations

60
Recent Advances in Grey Wolf Optimizer, its Versions and Applications: Review DOI Creative Commons
Sharif Naser Makhadmeh, Mohammed Azmi Al‐Betar, Iyad Abu Doush

et al.

IEEE Access, Journal Year: 2023, Volume and Issue: 12, P. 22991 - 23028

Published: Aug. 14, 2023

The Grey Wolf Optimizer (GWO) has emerged as one of the most captivating swarm intelligence methods, drawing inspiration from hunting behavior wolf packs. GWO's appeal lies in its remarkable characteristics: it is parameter-free, derivative-free, conceptually simple, user-friendly, adaptable, flexible, and robust. Its efficacy been demonstrated across a wide range optimization problems diverse domains, including engineering, bioinformatics, biomedical, scheduling planning, business. Given substantial growth effectiveness GWO, essential to conduct recent review provide updated insights. This delves into GWO-related research conducted between 2019 2022, encompassing over 200 articles. It explores GWO terms publications, citations, domains that leverage potential. thoroughly examines latest versions categorizing them based on their contributions. Additionally, highlights primary applications with computer science engineering emerging dominant domains. A critical analysis accomplishments limitations presented, offering valuable Finally, concludes brief summary outlines potential future developments theory applications. Researchers seeking employ problem-solving tool will find this comprehensive immensely beneficial advancing endeavors.

Language: Английский

Citations

57
A Novel Decomposition-Based Multi-Objective Symbiotic Organism Search Optimization Algorithm DOI Creative Commons

N. Ganesh,

Rajendran Shankar,

Kanak Kalita

et al.

Mathematics, Journal Year: 2023, Volume and Issue: 11(8), P. 1898 - 1898

Published: April 17, 2023

In this research, the effectiveness of a novel optimizer dubbed as decomposition-based multi-objective symbiotic organism search (MOSOS/D) for problems was explored. The proposed based on organisms’ (SOS), which is star-rising metaheuristic inspired by natural phenomenon symbioses among living organisms. A decomposition framework incorporated in SOS stagnation prevention and its deep performance analysis real-world applications. investigation included both qualitative quantitative analyses MOSOS/D metaheuristic. For analysis, statistically examined using it to solve unconstrained DTLZ test suite real-parameter continuous optimizations. Next, two constrained structural benchmarks optimization scenario were also tackled. performed characteristics Pareto fronts, boxplots, dimension curves. To check robustness optimizer, comparative carried out with four state-of-the-art optimizers, viz., MOEA/D, NSGA-II, MOMPA MOEO, grounded six widely accepted measures. feasibility Friedman’s rank demonstrates dominance over other compared techniques exhibited solving large complex problems.

Language: Английский

Citations

44