Multi-objective optimization framework for electric vehicle charging and discharging scheduling in distribution networks using the red deer algorithm by Sahbi Boubaker, Habib Kraiem, Nejib Ghazouani, Souad Kamel, Adel Mellit, Faisal S. Alsubaei, Farid Bourennani, Walid Meskine, Tariq Alqubaysi

“…To tackle the optimization problem, a metaheuristic swarm intelligence algorithm, the Red Deer Algorithm (RDA), is utilized to determine the optimal EV charging and discharging timings. …”
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A Framework for Low-Carbon Container Multimodal Transport Route Optimization Under Hybrid Uncertainty: Model and Case Study by Fenling Feng, Fanjian Zheng, Ze Zhang, Lei Wang

“…Subsequently, a multi-strategy improved whale optimization algorithm (WOA) is developed to solve the formulated model. …”
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Enhanced Pure Pursuit Path Tracking Algorithm for Mobile Robots Optimized by NSGA-II with High-Precision GNSS Navigation by Xiongwen Jiang, Taiga Kuroiwa, Yu Cao, Linfeng Sun, Haohao Zhang, Takahiro Kawaguchi, Seiji Hashimoto

“…The improved algorithm considers the dynamic characteristics and real–world operating conditions of the robot, optimizing steering decisions to enhance path tracking accuracy. …”
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FedDyH: A Multi-Policy with GA Optimization Framework for Dynamic Heterogeneous Federated Learning by Xuhua Zhao, Yongming Zheng, Jiaxiang Wan, Yehong Li, Donglin Zhu, Zhenyu Xu, Huijuan Lu

“…Prior to this work, few studies have explored the use of optimization algorithms for hyperparameter tuning in federated learning. …”
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Optimal AC Power Flow with Energy Storage and Renewable Energy: An Efficient RL Algorithm Capable of Handling Equality Constraints by Mingde Liu, Jianquan Zhu, Mingbo Liu

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Comparative Analysis of Some Methods and Algorithms for Traffic Optimization in Urban Environments Based on Maximum Flow and Deep Reinforcement Learning by Silvia Baeva, Nikolay Hinov, Plamen Nakov

“…This paper presents a comparative analysis between classical maximum flow algorithms and modern deep Reinforcement Learning (RL) algorithms applied to traffic optimization in urban environments. …”
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Cost-Effective Optimization of Sizing and Charging Profiles for PHEV Parking Lots in Smart Microgrids Using Harmony Search Algorithm by Mehrdad Ahmadi Kamarposhti, Hassan Shokouhandeh, Emad M. Ahmed, Zaki A. Zaki, Ilhami Colak, El Manaa Barhoumi, Kei Eguchi

“…This paper presents an optimization approach for managing the charging and discharging of electric vehicles (EVs) in parking lots using the Harmony Search (HS) and Differential Evolution (DE) algorithms. …”
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A quasi oppositional forensic based investigation algorithm for optimizing distributed generation placement and sizing in power distribution systems by Binaya Kumar Malika, Vivekananda Pattanaik, Subhasis Panda, Binod Kumar Sahu, Pravat Kumar Rout, Mohit Bajaj, Vojtech Blazek, Lukas Prokop, Stanislav Misak

“…This manuscript addresses these issues by proposing a novel quasi-oppositional forensic-based investigation (QOFBI) algorithm, an evolutionary meta-optimization technique designed to optimize the location and sizing of DGs under various operating conditions, while adhering to system constraints. …”
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Rotation Correction Algorithm Based on Polar Harmonic Fourier Moments and Optimization of Color Image Security Quantization Watermarking Scheme by Yuli Yang, Meiru Jiang, Xiufang Feng, Chenchen Lu, Yongle Chen, Shuang Zhou, Hao Zhang

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Comprehensive optimization of active and reactive power scheduling in smart microgrids by accounting for line transmission losses using genetic algorithm by F.Z. Zahraoui, H.E. Chakir, M. Et-taoussi, H Ouadi

“…The grid-connected SMG consists of photovoltaic (PV) cells, BSS, and residential loads. A Genetic Algorithm (GA)-based method is proposed to optimize power management in three scenarios: (i) active power only (AOM), (ii) active and reactive power without line losses (ARM), and (iii) active and reactive power considering line losses (ARLM). …”
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Multi-Degree Reduction of Said–Ball Curves and Engineering Design Using Multi-Strategy Enhanced Coati Optimization Algorithm by Feng Zou, Xia Wang, Weilin Zhang, Qingshui Shi, Huogen Yang

“…To enhance performance further, we propose a multi-strategy enhanced coati optimization algorithm (MSECOA). This algorithm utilizes a good point set combined with opposition-based learning to refine the initial population distribution, employs a fitness–distance equilibrium approach alongside a dynamic spiral search strategy to harmonize global exploration with local exploitation, and integrates an adaptive differential evolution mechanism to boost convergence rates and robustness. …”
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Optimizing a Hybrid Controller for Automotive Active Suspension System by Using Genetic Algorithms With Two High Level Parameters by Vu Van Tan, Do Trong Tu, Nguyen Van Vinh, Pham Tat Thang, Andras Mihaly, Peter Gaspar

“…Specifically, the ride comfort has improved from 60% to 80%, while the road holding has improved from 10% to 15%. …”
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Dual-layer scheduling coordination algorithm for power supply guarantee using multi-objective optimization in spot market environment by Xuanyuan Wang, Xu Gao, Zhen Ji, Wei Sun, Bo Yan, Bohao Sun

“…The experimental results show that, compared to the benchmark strategy, the proposed algorithm achieves a cost savings of 8.33% while ensuring a reliable power supply. …”
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Optimization of Francis turbine runner based on analytic hierarchy process – entropy weight method and multi-objective Lichtenberg algorithm by Xiaobo Zheng, Wei Wang, Yaping Zhao, Hao Liang, Pengcheng Guo, Zhihua Li

“…To address these issues, this study develops a multi-condition, multi-objective optimization platform for a Francis turbine runner based on the Analytic Hierarchy Process-Entropy Weight (AHP) method and the Multi-Objective Lichtenberg Algorithm (MOLA). …”
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Estimating Daily Reference Crop Evapotranspiration in Northeast China Using Optimized Empirical Models Based on Heuristic Intelligence Algorithms by Zongyang Li, Zhengxin Zhao, Liwen Xing, Lu Zhao, Ningbo Cui, Huanjie Cai

“…By using the least square method (LSM) and three population heuristic intelligent algorithms—a genetic algorithm (GA), a particle swarm optimization algorithm (PSO), and a differential evolution algorithm (DE)—the parameters of eleven kinds of models were optimized, respectively, and the ETo estimation model suitable for northeast China was selected. …”
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The quick crisscross sine cosine algorithm for optimal FACTS placement in uncertain wind integrated scenario based power systems by Sunilkumar P. Agrawal, Pradeep Jangir, Laith Abualigah, Sundaram B. Pandya, Anil Parmar, Absalom E. Ezugwu, Arpita, Aseel Smerat

“…The Quick Crisscross Sine Cosine Algorithm (QCSCA) was developed to address the challenges of solving the Optimal Power Flow (OPF) problem in power systems that integrate renewable energy sources and Flexible AC Transmission Systems (FACTS) devices. …”
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Hyperparameter Optimization for Problem-Based Custom CNN Architectures Using a Smart Grid Search Method by H. Aktas

“…The proposed method was also compared with Bayesian optimization using a similar search space. While Bayesian optimization achieved the same highest test accuracy (99.22%), it produced a model that was 3.7 times larger. …”
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Enhanced energy-efficient cluster-based routing with spotted hyena optimization in heterogeneous WSNs by Ved Prakash, Suman Pandey, Biswa Mohan Sahoo

“…The proposed SHO-CH method seeks to improve energy efficiency and prolong the lifespan of the network by optimizing the development of clusters and routing. …”
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Solving the Economic Load Dispatch Problem by Attaining and Refining Knowledge-Based Optimization by Pravesh Kumar, Musrrat Ali

“…The Static Economic Load Dispatch (SELD) problem is a paramount optimization challenge in power engineering that seeks to optimize the allocation of power between generating units to meet imposed constraints while minimizing energy requirements. …”
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Bone scintigraphy based on deep learning model and modified growth optimizer by Omnia Magdy, Mohamed Abd Elaziz, Abdelghani Dahou, Ahmed A. Ewees, Ahmed Elgarayhi, Mohammed Sallah

“…In addition, the second phase is named feature selection, and it is dependent on the Arithmetic Optimization Algorithm (AOA) being used to improve the Growth Optimizer (GO). …”
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