Multi-Focus Image Fusion Using Energy Valley Optimization Algorithm by Harun Akbulut

“…The obtained experimental results are compared with the well-known Genetic Algorithm (GA), Differential Evolution Algorithm (DE), and Artificial Bee Colony Optimization Algorithm (ABC). …”
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A novel robust multi-objective evolutionary optimization algorithm based on surviving rate by Wenxiang Jiang, Kai Gao, Shuwei Zhu, Lihong Xu

“…Despite the success of multi-objective evolutionary optimization algorithms in addressing complex optimization problems, research focusing on input disturbances remains limited. …”
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A Hybrid Optimization Algorithm for the Synthesis of Sparse Array Pattern Diagrams by Youzhi Liu, Linshu Huang, Xu Xie, Huijuan Ye

“…The algorithm enhances global search capability through the introduction of a quantum potential well model, while incorporating adaptive mutation operations to prevent premature convergence, thereby improving optimization accuracy during later iterations. …”
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Polar lights optimizer: A novel algorithm for accurate parameter estimation in proton exchange membrane fuel cells by Mohammad Aljaidi, Pradeep Jangir, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Ali Fayez Alkoradees, Mohammad Khishe, Reena Jangid

“…The PLO algorithm generates SSE results of 0.025493 for BCS 500 W and 0.275211 for Nedstack 600 W PS6 and 0.283774 for STD 250 W Stack while keeping AE at 0.259293 and RE% at 1.185075 for the STD 250 W Stack. …”
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A Comparison of Metaheuristic Algorithms for Structural Optimization: Performance and Efficiency Analysis by Saeedeh Ghaemifard, Amin Ghannadiasl

“…This paper conducts a comparative analysis of meta-heuristic algorithms applied to structural optimization. It encompasses 11 distinct meta-heuristic optimization algorithms: atomic orbital search algorithm, chaos game optimization, energy valley optimizer, firefly algorithm, genetic algorithm, gray wolf optimization, harmony search, material generation algorithm, particle swarm optimization, social network search, and whale optimization algorithm. …”
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Route Optimization for UGVs: A Systematic Analysis of Applications, Algorithms and Challenges by Dario Fernando Yépez-Ponce, William Montalvo, Ximena Alexandra Guamán-Gavilanes, Mauricio David Echeverría-Cadena

“…Heuristic algorithms, such as Humpback Whale Optimization, Firefly Search and Particle Swarm Optimization, are commonly employed to solve complex search problems. …”
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Discrete Sizing Optimization of Steel Structures Using Modified Fireworks Algorithm by Navid Seraji, Mehdi Babaei

“…A total of six benchmark structures including a 10-bar truss, a 25-bar truss, a 582-bar tower truss, a two-bay three-story frame, a one-bay 10-story frame, and a three-bay 24-story frame are chosen from previous studies for the optimization. In addition, a comparison is presented between the results of MoFWA with FWA and other optimization methods such as modified sine-cosine algorithm (MSCA), newton meta-heuristic algorithm (NMA), improved grey wolf optimizer (GWOM), enhanced whale optimization algorithm (EWOA), switching teams algorithm (STA), MHBMO, artificial bee colony (ABC), school-based optimization (SBO), teaching-learning based optimization (TLBO), design-driven harmony search (DDHS), and inscribed hyperspheres (IHS). …”
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A hybrid particle swarm optimization algorithm for solving engineering problem by Jinwei Qiao, Guangyuan Wang, Zhi Yang, Xiaochuan Luo, Jun Chen, Kan Li, Pengbo Liu

“…Finally, the algorithm applies the spiral shrinkage search strategy from the whale optimization algorithm (WOA) and the Differential Evolution (DE) mutation strategy in the later iteration to accelerate the convergence speed. …”
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Optimizing Trajectories for Rechargeable Agricultural Robots in Greenhouse Climatic Sensing Using Deep Reinforcement Learning with Proximal Policy Optimization Algorithm by Ashraf Sharifi, Sara Migliorini, Davide Quaglia

“…In this paper, we propose a method based on Deep Reinforcement Learning enriched with a Proximal Policy Optimization (PPO) algorithm for determining the best trajectory an agricultural robot must follow to balance the number of measurements and autonomy adequately. …”
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An Improved Multi-Objective Adaptive Human Learning Optimization Algorithm and Its Application in Optimizing Formulation Schemes for Rotary Hearth Furnaces by Jun Yao, Songcheng Zhou, Ling Wang, Xianxia Zhang

“…An improved multi-objective adaptive human learning optimization algorithm (IMOAHLO) is proposed, which enhances local optimization through neighborhood search and an adaptive learning mechanism. …”
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An efficient metaheuristic optimization algorithm for optimal power extraction from PV systems under various weather and load-changing conditions by Md.Al Imran Fahim, Md.Salah Uddin Yusuf, Monira Islam, Munshi Jawad Ibne Azad

“…To address these challenges, a new algorithm called horse herd optimization (HHO) has been applied to the maximum power point tracking (MPPT) controller. …”
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A Group Search Algorithm for Optimal Scheduling of Cascade Hydropower Stations by WANG Kechao, CAI Ruoyi, SHEN Jianjian

“…The coronavirus herd immunity optimizer (CHIO) algorithm was introduced to address the optimal scheduling problem of cascade hydropower plants, and an improved algorithm called LCHIO was proposed. …”
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A Group Search Algorithm for Optimal Scheduling of Cascade Hydropower Stations by WANG Kechao, CAI Ruoyi, SHEN Jianjian

“…The coronavirus herd immunity optimizer (CHIO) algorithm was introduced to address the optimal scheduling problem of cascade hydropower plants, and an improved algorithm called LCHIO was proposed. …”
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An Improved Coral Reef Optimization-Based Scheduling Algorithm for Cloud Computing by Shuzhen Wan, Lixin Qi

“…In this paper, we establish a resource allocation framework and propose a novel task scheduling algorithm. An improved coral reef optimization (ICRO) is proposed to deal with this task scheduling problem. …”
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Application of Blocplan and Aldep Algorithms for Optimizing Production Layout at Meatball Factory by Thabed Tholib Baladraf

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Modification of the genetic algorithm for comprehensive topological optimization of the synchronous motors rotor by T. I. Petrov

“…The aim is to develop a methodology for topological complex optimization of the engine design, based on a genetic algorithm.METHODS. …”
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EG-DPoS: Optimized DPoS Consensus Algorithm Based on Evolutionary Game by LIU Yong, DENG Xiaohong, LIU Lihui, SHI Yiran, ZHANG Li

“…Aiming at the problems of low enthusiasm among voting nodes, bribery from malicious nodes, and the vulnerability of sequential block generation by agent nodes in the delegated proof of stake (DPoS) consensus process, an optimized DPoS consensus algorithm based on evolutionary game theory (EG-DPoS) is proposed. …”
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Research on Algorithms for Local Robot Positioning Using Methods of Discrete Optimization by Vyacheslav Korolyov, Maksim Ogurtsov, Oleksandr Khodzinskyi

“…For constructing the relative coordinate system, a method of forming a base triangle using a nonlinear discrete optimization method was proposed. An algorithm for building a local positioning system for a robot group was developed to ensure the stable configuration of the group in the absence of access to global or cellular navigation systems while performing tasks in two-dimensional spaces. …”
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Research on Pose Error Modeling and Compensation of Posture Adjustment Mechanism Based on WOA-RBF Neural Network by Hongyu Shen, Honggen Zhou, Yiyang Jin, Lei Li, Bo Deng, Jiawei Xu

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Research on performance optimizations for TCM-KNN network anomaly detection algorithm by LI Yang1, GUO Li1, LU Tian-bo3, TIAN Zhi-hong1

“…Based on TCM-KNN（transductive confidence machine for K-nearest neighbors） algorithm,the filter-based feature selection and cluster-based instance selection methods were used towards optimizing it as a lightweight network anomaly detection scheme,which not only reduced its complex feature space,but also acquired high quality instances for training.A series of experimental results demonstrate the two methods for optimizations are actually effective in greatly reducing the computational costs while ensuring high detection performances for TCM-KNN algorithm.Therefore,the two methods make TCM-KNN be a good scheme for a lightweight network anomaly detection in practice.…”
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