Multiobjective Optimization of Large-Scale EVs Charging Path Planning and Charging Pricing Strategy for Charging Station by Weicheng Hou, Qingsong Luo, Xiangdong Wu, Yimin Zhou, Gangquan Si

“…Then, a particle swarm optimization (PSO) algorithm is applied to solve the optimal solution of charging station pricing designation. …”
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Securing Electrical Drive Systems Against Man-in-the-Middle Attacks Using S-Box Optimized AES Encryption by J. Dheeba, Vansh Oberoi, R. Raja Singh, V. Gautam Karthik

“…The optimization performance is evaluated using nonlinearity, avalanche effect, and bit independence metrics, while the AES algorithm’s performance is analyzed in terms of encryption throughput and latency. …”
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A spectral Fletcher-Reeves conjugate gradient method with integrated strategy for unconstrained optimization and portfolio selection. by Nasiru Salihu, Sulaiman M Ibrahim, P Kaelo, Issam A R Moghrabi, Elissa Nadia Madi

“…Numerical experiments performed on some unconstrained optimization problems highlight the superiority of this new algorithm over certain CG methods with similar characteristics. …”
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Optimized exposer region-based modified adaptive histogram equalization method for contrast enhancement in CXR imaging by Shivam Gangwar, Reeta Devi, Nor Ashidi Mat Isa

“…Each region undergoes adaptive contrast enhancement via a novel weighted probability density function (PDF) and power-law transformation to ensure balanced enhancement across different exposure levels. The PSO algorithm is then employed to optimize power-law parameters, further refining contrast enhancement and illumination uniformity while maintaining the natural appearance of medical images. …”
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Joint Beamforming, Scheduling, Trajectory, and Transmit Power Optimization in UAV-Assisted ISAC Systems for Information Freshness by Yuting He, Qingjie Wu, Miao Cui, Yuan Peng, Guangchi Zhang, Wei Chen

“…Our objective is to minimize the age of information (AoI) of the sensory data by jointly optimizing the scheduling, transmit beamforming, trajectory, and transmit power of the UAV, while considering the communication quality constraints and physical constraints. …”
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Recursive Objective Space Exploration (ROSE): A computationally efficient deterministic approach for bi-objective optimization. by Ihab Hashem, Viviane De Buck, Seppe Seghers, Jan Van Impe

“…Our approach is inspired by how plants efficiently explore physical space in search of light energy, balancing exploration and exploitation while minimizing biomass cost. The algorithm navigates the objective space without revisiting previously explored areas by solving intermediate SOOPs visualized as branches within this space. …”
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A multi-objective aerodynamic performance optimization of a centrifugal vacuum pump and the flow physics analysis by Zhanyuan Gu, Jiangtao Zhang, Wei Zhang, Yikun Wei

“…The backpropagation neural network was employed as the surrogate model, and the multi-objective optimization was performed using the non-dominated sorting genetic algorithm. …”
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Optimizing Distribution Grid Performance through Electric Vehicle Integration and Stochastic Modeling in Extreme Weather Conditions by A. Niknami, M. Askari, M. Amirahmadi, M. Babaeinik

“…Monte Carlo simulation is employed to model uncertainties, while a multi-objective optimization algorithm is used to solve the problem. …”
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Optimization of D2D emergency communication resources for UAV relay based on DA-STD3 by Xiaofang Deng, Zijian Deng, Lin Zheng, Chao Yang, Chuanxu Chen

“…Abstract The allocation of communication resources is extremely important for the device-to-device (D2D) communication network with unmanned aerial vehicle (UAV) relays, but this field currently mainly focuses on the communication between UAVs and ground devices. While neglecting the comprehensive optimization of air-to-ground communication and internal ground communication. …”
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Multi-Objective Optimization of Parking Charging Strategy for Extended-Range Hybrid Electric Vehicle Based on MOMSA by Rong Yang, Jianxiang Lu, Zhiqi Sun, Wei Huang

“…This study addresses this gap by developing a novel parking charging strategy for E-RHEVs that leverages a temperature-dependent battery aging model and a Multi-Objective Mantis Search Algorithm (MOMSA)—a metaheuristic optimization algorithm designed to solve multi-objective problems by efficiently exploring trade-offs between conflicting objectives. …”
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An optimized spatial target trajectory prediction model for multi-sensor data fusion in air traffic management by Jian Dong, Yuan Xu, Rigeng Wu, Chengwang Xiao

“…The improved snow ablation optimizer algorithm optimizes hyperparameters of this network automatically, while the multi-head attention mechanism redistributes weighted features, integrating them into comprehensive features. …”
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Sperm swarm optimization for many objective power flow problems with enhanced performance evaluation in power systems by Wulfran Fendzi Mbasso, Ambe Harrison, Pradeep Jangir, Idriss Dagal, Hossam Kotb, Njimboh Henry Alombah, Raman Kumar, Aseel Smerat, Emmanuel Fendzi Donfack, Saad F. Al-Gahtani, Z. M. S. Elbarbary

“…MaOSSO is shown to consistently outperform competing methods with up to 15–20% faster convergence and 25% less computation time. While applying the algorithm on the MaO-OPF problem, the active/reactive power loss minimization was optimized along with the voltage stability, emissions, operational cost, and Pareto front diversity sustaining. …”
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Joint optimization method for UAV trajectory and charging/discharging in cell-free mMIMO system on WPT by WANG Qin, NING Luohan, ZHANG Yuxuan, LIU Ying, CAI Yan, ZHAO Haitao

“…Simulation results demonstrate that, while balancing endurance and communication requirements, this algorithm significantly elevates the utilization rate of UAV and enhances communication fairness for interrupted user equipment (UE), ultimately achieving dynamic regional coverage.…”
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DRL-based max-min fair RIS discrete phase shift optimization for MISO-OFDM systems by Peng Chen, Huaqian Zhang, Xiao Li, Shi Jin

“…Simulation results demonstrate that the proposed DRL-based algorithm can achieve almost optimal performance, while has much less computation consumption.…”
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Enhancing Smart and Zero-Carbon Cities Through a Hybrid CNN-LSTM Algorithm for Sustainable AI-Driven Solar Power Forecasting (SAI-SPF) by Haytham Elmousalami, Felix Kin Peng Hui, Aljawharah A. Alnaser

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A Cloud-Edge-End Collaboration Framework for Fixed-Time Distributed Optimization of Virtual Power Plants by Kai Kang, Nian Shi, Keqi Zhang, Si Cai, Liang Zhang, Xinan Shao, Lei Shu, Renjie Hu, Leimin Wang

“…This framework enables parallel computation of multiple distributed optimization algorithms. Additionally, a distributed fixed-time optimization consensus algorithm is designed for virtual power plants, allowing the convergence time to be predetermined offline. …”
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Optimization for Metro Operation Scheme of Suburban Lines: A New Method for Dealing with the Imbalanced Passenger Flow by Xiaobing Ding, Gan Shi, Jiangang Jin, Lixing Yang, Zhigang Liu

“…Suburban lines with imbalanced passenger flow between stations will lead to extremely crowded passenger flow in some stations, while scarce passenger flow in other stations. To balance the train’s carrying capacity with the imbalanced passenger flow, this study explores the collaborative optimization of train operation under the new mode of express and local. …”
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Energy-Efficient Optimization of mm-Wave Communication Using a Novel Approach of Beamspace MIMO-NOMA by Ammar A. Majeed, Ismail Hburi

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Model-based quantitative analysis in two-time-scale decomposed on–off optimal control of greenhouse cultivation by Dan Xu, Yanfeng Li, Anguo Dai, Shumei Zhao, Weitang Song

“…These setpoints cannot guarantee maximum profit, which can be treated as the control objective of the optimal control algorithm. This paper investigated on–off optimal control algorithms based on two-time-scale decomposition. …”
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Intelligent Flight Procedure Design: A Reinforcement Learning Approach with Pareto-Based Multi-Objective Optimization by Yunyang Huang, Yanxin Zhang, Yandong Zhu, Zhuo Zhang, Longtao Zhu, Hongyu Yang, Yulong Ji

“…To further enhance performance by tackling the low sampling efficiency in the replay buffer, we introduce a multi-objective sampling strategy based on the Pareto frontier, integrated with the soft actor–critic (SAC) algorithm. Experimental results demonstrate that the proposed method generates executable flight procedures in the BlueSky open-source flight simulator, successfully balancing these three conflicting objectives, while achieving a 28.6% increase in convergence speed and a 4% improvement in comprehensive performance across safety, route simplification, and environmental impact compared to the baseline algorithm. …”
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