An Environmentally Adaptive CRO-SL Algorithm Based on Dynamic Agents for the Channel Assignment Problem in Wireless Networks by Antonio J. Romero-Barrera, Luis Cruz-Piris, Marino Tejedor-Romero, Jose Manuel Gimenez-Guzman, Ivan Marsa-Maestre

“…The Environmentally Adaptive CRO-SL (EnvAdapt-CRO-SL) implementation aims to improve solution exploration, enhancing computational efficacy in generating new candidate solutions within the coral reef population. An exhaustive comparative analysis of four configurations of the proposed EnvAdapt-CRO-SL variant assesses the impact of each environmental agent on the algorithm’s performance. …”
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A multiobjective evolutionary algorithm incorporating neighborhood detection for the vehicle routing problem with soft time windows by Hao Jiang, Zhiwei Zhang, Chao Wang, Xiaoshu Xiang

“…Abstract The Vehicle Routing Problems with Soft Time Windows (VRPSTWs) presents a common challenge in practical scenarios, which has spurred the development of various algorithmic solutions. Among these solutions, hybrid approaches that integrate evolutionary algorithms and neighborhood search techniques have shown great promise. …”
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Optimal Reactive Power Generation for Radial Distribution Systems Using a Highly Effective Proposed Algorithm by Le Chi Kien, Thuan Thanh Nguyen, Bach Hoang Dinh, Thang Trung Nguyen

“…In this paper, a proposed modified stochastic fractal search algorithm (MSFS) is applied to find the most appropriate site and size of capacitor banks for distribution systems with 33, 69, and 85 buses. …”
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Zebra optimization algorithm incorporating opposition-based learning and dynamic elite-pooling strategies and its applications. by Tengfei Ma, Guangda Lu, Zhuanping Qin, Tinghang Guo, Zheng Li, Changli Zhao

“…To address the limitations of the Zebra Optimization Algorithm (ZOA), including insufficient late-stage optimization search capability, susceptibility to local optima, slow convergence, and inadequate exploration, this paper proposes an enhanced Zebra Optimization Algorithm integrating opposition-based learning and a dynamic elite-pooling strategy (OP-ZOA: Opposition-Based Learning Dynamic Elite-Pooling Zebra Optimization Algorithm). he proposed search algorithm employs a good point set-elite opposition-based learning mechanism to initialize the population, enhancing diversity and facilitating escape from local optima. …”
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DMPDS: A Fast Motion Estimation Algorithm Targeting High Resolution Videos and Its FPGA Implementation by Gustavo Sanchez, Felipe Sampaio, Marcelo Porto, Sergio Bampi, Luciano Agostini

“…The new Dynamic Multipoint Diamond Search (DMPDS) algorithm is a fast algorithm which increases the ME quality when compared with other fast ME algorithms. …”
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Distributed hybrid energy storage photovoltaic microgrid control based on MPPT algorithm and equilibrium control strategy by Yanlong Qi, Rui Liu, Haisheng Lin, Junchen Zhong, Zhen Chen

“…In the performance comparison analysis of the research algorithm, the average accuracy and average loss value of the algorithm were 98.2% and 0.15, respectively, which were significantly better than the compared algorithms. …”
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Equitable post-disaster relief distribution: a robust multi-objective multi-stage optimization approach by Sogand Soghrati Ghasbeh, Nadia Pourmohammadzia, Masoud Rabbani

“…Design/methodology/approach – A hybrid algorithm of adaptive large neighborhood search (ALNS) and multi-dimensional local search (MDLS) is introduced to solve the problem. …”
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Improved Artificial Bee Colony Optimization Underwater Localization Algorithm by Logistic Chaos Mapping and Differential Evolution by Jiaxing CHEN, Yang LIU, Xiaoqian LIU, Zhihua LIU

“…This new algorithmic approach was developed with a particular focus on the population initialization phase and the leading bee search phase. …”
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An Enhanced Semisteady-State Jaya Algorithm With a Control Coefficient and a Self-Adaptive Multipopulation Strategy by Joshua Churchill Ankrah, Francis Boafo Effah, Elvis Twumasi

“…The Wilcoxon signed-rank test confirms the statistical significance of the overall rankings. When compared with the Snow Geese Algorithm (SGA), Big Bang–Big Crunch Algorithm (BBBCA), firefly algorithm (FA), bat algorithm (BA), cuckoo search algorithm (CSA), and flower pollination algorithm (FPA), the ESJaya algorithm gives competitive results in terms of obtaining optimum values, mean accuracy, and stability. …”
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Multi robot exploration using an advanced multi-objective salp swarm algorithm for efficient coverage and performance by Ali El Romeh, Seyedali Mirjalili

“…AMET combines the deterministic structure of Coordinated Multi-Robot Exploration (CME) with the adaptive search capabilities of the Multi-Objective Salp Swarm Algorithm (MSSA) to achieve a balanced trade-off between exploration efficiency and mapping accuracy. …”
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An improved multi-objective artificial physics optimization algorithm based on R2 indicator and its application by Bao Sun, Yihong Chang, Min Gao, Zhanlong Li, Jiankang Liu, Jinbin Wang

“…It also dynamically adjusts inertia weights and gravitational factors to enhance its global and local search capabilities. To evaluate the performance of the R2-ICRMOAPO algorithm, we compared it with four other multi-objective optimization algorithms using standard test functions. …”
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A new modified incomprehensible but intelligible-in-time logics algorithm for modeling solid oxide fuel cell by Shahr Alshahr, Fatma A. Hashim, Ahmed Alshahir, Ahmed Fathy, Hegazy Rezk

“…Also, new approaches of Aquila optimizer (AO), Chef-based optimization algorithm (CBOA), African vultures optimization approach (AVOA), gold rush optimizer (GRO), transient search optimizer (TSO), osprey optimization approach (OOA), and traditional ILA are programmed to assess the proposed strategy. …”
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Oil well productivity capacity prediction based on support vector machine optimized by improved whale algorithm by Kuiqian Ma, Chunxin Wu, Yige Huang, Pengfei Mu, Peng Shi

“…Residual sum of squares (R2) values for SVM optimized by grid search optimization, whale algorithm and improved whale algorithm are 0.372, 0.939 and 0.941 respectively. …”
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Optimization of High-Speed Train Control Strategy for Traction Energy Saving Using an Improved Genetic Algorithm by Ruidan Su, Qianrong Gu, Tao Wen

“…Train traction property and braking property was explored detailed to ensure the accuracy of running. The PMPGA was also compared with the standard genetic algorithm (SGA); the influence of the fitness function representation on the search results was also explored. …”
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Optimal D-STATCOM placement and sizing using a novel bird swarm operated exploitation of elephant herd algorithm by V. Tejaswini, D. Susitra

“…The proposed Hybrid Algorithm, named Bird Swarm Operated Exploitation of Elephant Herd (BSOEEH), is tested under four different scenarios to determine its effectiveness compared to traditional optimization methods. …”
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Deep deterministic policy gradient algorithm based on dung beetle optimization and priority experience replay mechanism by Hengwei Zhu, Chuiting Rong, Haorui Liu

“…This method first adopts the simultaneous search policy of multiple populations by introducing the dung beetle optimizer (DBO), which can effectively keep the algorithm from falling into the local optimum solution and improve global optimization capability. …”
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Prediction of Insulator ESDD Based on Meteorological Feature Mining and AdaBoost-MEA-ELM Model by Yaoping WANG, Te LI, Kaihua JIANG, Wenhui LI, Qiang WU, Yu WANG

“…The meteorological features that are more closely related to insulator pollution degree are mined, and the importance of each meteorological feature is evaluated by the random forest algorithm. Combined with the sequential forward search method, the optimal subset of meteorological features for ESDD prediction model could be determined. …”
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Multi-UAV Trajectory Optimization Under Dynamic Threats: An Enhanced GWO Algorithm Integrating a Priori and Real-Time Data by Zihan Zhou, Yanhong Guo, Yitao Wang, Jingfan Lyu, Haoran Gong, Xin Ye, Yachao Li

“…Experimental results demonstrate that the dynamic threat zone crossing strategy significantly reduces trajectory costs compared to the traditional bypass strategy. Furthermore, the enhanced GWO algorithm outperforms both the traditional GWO and MP-GWO algorithms in terms of trajectory cost and convergence accuracy. …”
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Energy management strategy for methanol hybrid commercial vehicles based on improved dung beetle algorithm optimization. by Zhihao Li, Ping Xiao, Jiabao Pan, Wenjun Pei, Aoning Lv

“…This integration compensates for the traditional dung beetle algorithm's tendency to fall into local optima and enhances its global search capability. …”
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Research on the Application of Variational Mode Decomposition Optimized by Snake Optimization Algorithm in Rolling Bearing Fault Diagnosis by Houxin Ji, Ke Huang, Chaoquan Mo

“…Finally, this method is used to analyze the simulation signal and rolling bearing vibration signal and compared with empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), and complete ensemble empirical mode decomposition adaptive noise (CEEMDAN) algorithms to verify the feasibility and effectiveness of the SOA-VMD method.…”
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