Investigation of a Multi-Strategy Ensemble Social Group Optimization Algorithm for the Optimization of Energy Management in Electric Vehicles by Aala Kalananda Vamsi Krishna Reddy, Komanapalli Venkata Lakshmi Narayana

“…A multi-strategy ensemble social group optimization algorithm (ME-SGO) to improve the exploration for complex and composite landscapes through distance-based strategy adaption and success-based parameter adaption while incorporating linear population reduction is proposed. …”
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Scheduling optimization based on particle swarm optimization algorithm in emergency management of long-distance natural gas pipelines. by Huichao Guo, Runhua Huang, Shuqin Cheng

“…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …”
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An Improved Particle Swarm Optimization Algorithm forOptimal Allocation of Distributed Generation Units in Radial Power Systems by Neda Hantash, Tamer Khatib, Maher Khammash

“…The minimum value of fitness losses using the applied algorithm is found to be 0.0.0406 while the average elapsed time is 62.2325 s. …”
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Optimal adaptive heuristic algorithm based energy optimization with flexible loads using demand response in smart grid. by Hisham Alghamdi, Lyu-Guang Hua, Ghulam Hafeez, Sadia Murawwat, Imen Bouazzi, Baheej Alghamdi

“…MATLAB is used to do a load scheduling simulation for home appliances based on the OAWDO algorithm. By contrasting it with other algorithms, including the genetic algorithm (GA), the whale optimization algorithm (WOA), the fire-fly optimization algorithm (FFOA), and the wind-driven optimization (WDO) algorithms, the effectiveness of the OAWDO technique is supported. …”
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RUL Prediction of Rolling Bearings Based on Fruit Fly Optimization Algorithm Optimized CNN-LSTM Neural Network by Jiaping Shen, Haiting Zhou, Muda Jin, Zhongping Jin, Qiang Wang, Yanchun Mu, Zhiming Hong

“…In addition, introducing FOA enables the model to dynamically adjust the hidden layers and thresholds while optimizing the optimal path, thereby finding the best solution. …”
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Optimized conductor selection and phase balancing in unbalanced distribution networks: Economic optimization via the vortex search algorithm by Brandon Cortés-Caicedo, Jhony Andrés Guzmán-Henao, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña, Rubén Iván Bolaños

“…This methodology is compared against the hurricane optimization algorithm, the sine cosine algorithm, and the salp swarm optimization algorithm. …”
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Optimizing energy constrained target localization and tracking with radial bias and seeker optimization algorithms in wireless sensor networks by S. Yazhinian, S. Famila, P. Jose, Mahendar A, Sofia R

“…This paper proposes a novel approach combining Radial Bias (RB) with the Seeker Optimization Algorithm (SOA) to address the challenges of energy-constrained target localization and tracking. …”
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Energy-Efficient DC Power Traction Network Systems for Urban Mass Transportation: A Comparative Study of Optimization Algorithms by Dongxian Yu, Zhixin Wu, Lei Wang, Zaihui Cao, Hamdolah Aliev

“…To validate the proposed method, we compare the performance of the GWO algorithm with other optimization techniques, such as the Teaching-Learning-Based Optimizer (TLBO) and Differential Evolution (DE). …”
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Many-Objective Cheetah Optimizer: A Novel Paradigm for Solving Complex Engineering Problems by Pinank Patel, Divya Adalja, Nikunj Mashru, Pradeep Jangir, Arpita, Reena Jangid, G. Gulothungan, Ahmad O. Hourani, Kaznah Alshammari

“…MaOCO represents the Many-Objective Cheetah Optimization Algorithm which draws its concepts from the hunting behavior of cheetahs. …”
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Improving aquifer vulnerability assessment and its explainability in the Zanjan aquifer: Integrating DRASTIC model and optimized long short-term memory-based metaheuristic algorith... by Mojgan Bordbar, Khabat Khosravi, Changhyun Jun, Dongkyun Kim, Sayed M Bateni, Mahmood Safarzadeh, Hamid Kardan Moghaddam, Shohreh Azizi

“…The LSTM model was optimized using the particle swarm optimizer (PSO) and equilibrium optimizer (EO) metaheuristic algorithms. …”
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Rethinking Metaheuristics: Unveiling the Myth of “Novelty” in Metaheuristic Algorithms by Chia-Hung Wang, Kun Hu, Xiaojing Wu, Yufeng Ou

“…While nature-inspired optimization methods show promise for various applications, their effectiveness is often limited by metaphor-driven design, structural biases, and a lack of sufficient theoretical foundation. …”
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An improved dung beetle optimizer based on Padé approximation strategy for global optimization and feature selection by Tianbao Liu, Lingling Yang, Yue Li, Xiwen Qin

“…Feature selection is a crucial data processing method used to reduce dataset dimensionality while preserving key information. In this paper, we proposed a multi-strategy enhanced dung beetle optimization algorithm (mDBO) that integrates multiple strategies to effectively address the feature selection problem. …”
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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 novel metaheuristic optimizer GPSed via artificial intelligence for reliable economic dispatch by Mahmoud Ibrahim Mohamed, Ali M. Yousef, Ahmed A. Hafez

“…These meta-heuristic optimizers validate the proposed solver and confirm its applicability to any meta-heuristic optimization algorithm. …”
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Colonial bacterial memetic algorithm and its application on a darts playing robot by Szilárd Kovács, Csaba Budai, János Botzheim

“…Abstract In this paper, we present the Colonial Bacterial Memetic Algorithm (CBMA), an advanced evolutionary optimization approach for robotic applications. …”
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A similarity-based multi-objective test optimization technique using search algorithm by Amir Sohail Habib, Saif Ur Rehman Khan, Shahid Hussain, Naseem Ibrahim, Habib un Nisa, Abdullah Yousafzai

“…Inspired by this, we propose a Similarity-based Multi-Objective Optimization Technique (SMOOT) for test suite reduction using a Grey Wolf Optimizer (GWO) algorithm. …”
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A Mixed-Integer Convex Optimization Framework for Cost-Effective Conductor Selection in Radial Distribution Networks While Considering Load and Renewable Variations by Oscar Danilo Montoya, Oscar David Florez-Cediel, Luis Fernando Grisales-Noreña, Walter Gil-González, Diego Armando Giral-Ramírez

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A New Hybrid Grasshopper Optimization - Backpropagation for Feedforward Neural Network Training by Samer Alsammarraie, Nazar K. Hussein

“… The Grasshopper optimization algorithm showed a rapid converge in the initial phases of the global search, however while being around the global optimum, the searching process became so slow. …”
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Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization by Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

“…In addition, it examines 2,000 random surface soil samples, ranging from 0 to 20 cm, that were optimized using genetic algorithms (GA), particle swarm optimization (PSO), and Optuna. …”
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Space Trajectory Planning with a General Reinforcement-Learning Algorithm by Andrea Forestieri, Lorenzo Casalino

“…The proposed framework integrates Monte Carlo Tree Search with a neural network to efficiently explore and optimize space trajectories. While developed for space trajectory planning, the algorithm is broadly applicable to any problem involving hybrid action spaces. …”
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