Enhanced Flow Direction Arithmetic Optimization Algorithm for mathematical optimization problems with applications of data clustering DOI
Laith Abualigah, Khaled H. Almotairi, Mohamed Abd Elaziz

et al.

Engineering Analysis with Boundary Elements, Journal Year: 2022, Volume and Issue: 138, P. 13 - 29

Published: Feb. 15, 2022

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

246
Starling murmuration optimizer: A novel bio-inspired algorithm for global and engineering optimization DOI
Hoda Zamani, Mohammad H. Nadimi-Shahraki, Amir H. Gandomi

et al.

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

Published: Feb. 12, 2022

Language: Английский

Citations

231
Enhanced whale optimization algorithm for medical feature selection: A COVID-19 case study DOI
Mohammad H. Nadimi-Shahraki, Hoda Zamani, Seyedali Mirjalili

et al.

Computers in Biology and Medicine, Journal Year: 2022, Volume and Issue: 148, P. 105858 - 105858

Published: July 16, 2022

Language: Английский

Citations

211
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
A Bearing Fault Diagnosis Method Based on Wavelet Packet Transform and Convolutional Neural Network Optimized by Simulated Annealing Algorithm DOI Creative Commons

He Feng,

Qing Ye

Sensors, Journal Year: 2022, Volume and Issue: 22(4), P. 1410 - 1410

Published: Feb. 12, 2022

Bearings are widely used in various electrical and mechanical equipment. As their core components, failures often have serious consequences. At present, most parameter adjustment methods still manual adjustments of parameters. This method is easily affected by prior knowledge, falls into the local optimal solution, cannot obtain global requires a lot resources. Therefore, this paper proposes new for bearing fault diagnosis based on wavelet packet transform convolutional neural network optimized simulated annealing algorithm. Firstly, original vibration signal extracted to spectrogram, then obtained spectrogram sent adjustment, finally algorithm adjust To verify effectiveness method, database Case Western Reserve University testing, traditional intelligent compared. The results show that proposed has better more reliable effect than existing machine learning deep methods.

Language: Английский

Citations

91
A Feature Selection Based on the Farmland Fertility Algorithm for Improved Intrusion Detection Systems DOI

Touraj Sattari Naseri,

Farhad Soleimanian Gharehchopogh

Journal of Network and Systems Management, Journal Year: 2022, Volume and Issue: 30(3)

Published: March 19, 2022

Language: Английский

Citations

91
MFO-SFR: An Enhanced Moth-Flame Optimization Algorithm Using an Effective Stagnation Finding and Replacing Strategy DOI Creative Commons
Mohammad H. Nadimi-Shahraki, Hoda Zamani, Ali Fatahi

et al.

Mathematics, Journal Year: 2023, Volume and Issue: 11(4), P. 862 - 862

Published: Feb. 8, 2023

Moth-flame optimization (MFO) is a prominent problem solver with simple structure that widely used to solve different problems. However, MFO and its variants inherently suffer from poor population diversity, leading premature convergence local optima losses in the quality of solutions. To overcome these limitations, an enhanced moth-flame algorithm named MFO-SFR was developed global The introduces effective stagnation finding replacing (SFR) strategy effectively maintain diversity throughout process. SFR can find stagnant solutions using distance-based technique replaces them selected solution archive constructed previous effectiveness proposed extensively assessed 30 50 dimensions CEC 2018 benchmark functions, which simulated unimodal, multimodal, hybrid, composition Then, obtained results were compared two sets competitors. In first comparative set, well-known variants, specifically LMFO, WCMFO, CMFO, ODSFMFO, SMFO, WMFO, considered. Five state-of-the-art metaheuristic algorithms, including PSO, KH, GWO, CSA, HOA, considered second set. then statistically analyzed through Friedman test. Ultimately, capacity mechanical engineering problems evaluated latest 2020 test-suite. experimental statistical analysis confirmed superior algorithms for solving complex problems, 91.38% effectiveness.

Language: Английский

Citations

45
A Critical Review of Moth-Flame Optimization Algorithm and Its Variants: Structural Reviewing, Performance Evaluation, and Statistical Analysis DOI
Hoda Zamani, Mohammad H. Nadimi-Shahraki, Seyedali Mirjalili

et al.

Archives of Computational Methods in Engineering, Journal Year: 2024, Volume and Issue: 31(4), P. 2177 - 2225

Published: Feb. 2, 2024

Language: Английский

Citations

30
Recent Advances in Harris Hawks Optimization: A Comparative Study and Applications DOI Open Access
Abdelazim G. Hussien, Laith Abualigah,

Raed Abu Zitar

et al.

Electronics, Journal Year: 2022, Volume and Issue: 11(12), P. 1919 - 1919

Published: June 20, 2022

The Harris hawk optimizer is a recent population-based metaheuristics algorithm that simulates the hunting behavior of hawks. This swarm-based performs optimization procedure using novel way exploration and exploitation multiphases search. In this review research, we focused on applications developments well-established robust (HHO) as one most popular techniques 2020. Moreover, several experiments were carried out to prove powerfulness effectivness HHO compared with nine other state-of-art algorithms Congress Evolutionary Computation (CEC2005) CEC2017. literature paper includes deep insight about possible future directions ideas worth investigations regarding new variants its widespread applications.

Language: Английский

Citations

66