Optimization of Electric Vehicle Charging and Discharging Strategies Considering Battery Health State: A Safe Reinforcement Learning Approach by Shuifu Gu, Kejun Qian, Yongbiao Yang

“…Then, the EV charging and discharging decision-making problem, considering battery health status, is formulated as a constrained Markov decision process, and an interior-point policy optimization (IPO) algorithm based on long short-term memory (LSTM) neural networks is proposed to solve it. …”
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Uncertain Parameters Adjustable Two-Stage Robust Optimization of Bulk Carrier Energy System Considering Wave Energy Utilization by Weining Zhang, Chunteng Bao, Jianting Chen

“…By applying constraint linearization, the robust coordination model is formulated as a mixed-integer linear programming (MILP) problem and solved using an efficient solver. …”
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Energy Management of Industrial Energy Systems via Rolling Horizon and Hybrid Optimization: A Real-Plant Application in Germany by Loukas Kyriakidis, Rushit Kansara, Maria Isabel Roldán Serrano

“…While global deterministic and stochastic optimization methods are frequently used in practice, they often suffer from high computational costs and slow convergence, particularly when applied to large-scale, nonlinear problems with complex constraints. …”
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Multi-Scenario Stochastic Optimal Scheduling for Power Systems With Source-Load Matching Based on Pseudo-Inverse Laguerre Polynomials by Jiahao Ye, Lirong Xie, Lan Ma, Yifan Bian, Chuanshi Cui

“…This study uses HMORUN as a solution tool for the multi-objective stochastic optimization scheduling problem (MOSSP). This study uses constraint repair techniques to deal with the complex constraints of the MOSSP model to avoid system load shedding and minimize wind and photovoltaic generation curtailment. …”
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ISAR High Resolution Imaging Algorithm Based on Weighted Adaptive Mixed Norm by Q. Zhang, Q. Q. Chen, G. Xu, J. R. Chi

“…Meanwhile, the weight coefficients in this improved model can be iteratively updated in each cycle to improve the image reconstruction accuracy. The optimization model takes advantage of mixed norm to achieve fast convergence in the operation, and adopts conjugate gradient descent method and fast Fourier transform operation in the solution, which simplifies the solving process of the optimization problem and improves the operation efficiency of the algorithm. …”
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Data-Driven Distributionally Robust Optimization for Solar-Powered EV Charging Under Spatiotemporal Uncertainty in Urban Distribution Networks by Tianhao Wang, Xuejiao Zhang, Xiaolin Zheng, Jian Wang, Shiqian Ma, Jian Chen, Mengyu Liu, Wei Wei

“…Leveraging empirical datasets of EV usage and solar irradiance from a smart city deployment, the framework constructs Wasserstein ambiguity sets around historical distributions, enabling worst-case-aware decision-making without requiring the assumption of probability laws. The problem is formulated as a two-stage optimization model. …”
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Low-Voltage Power Restoration Based on Fog Computing Load Forecasting and Data-Driven Wasserstein Distributionally Robust Optimization by Ruoxi Liu, Yifan Song, Yuan Gui, Hanqi Dai, Zhiyong Wang, Chengdong Yin, Qinglei Qin, Wenqin Yang, Yue Wang

“…The column-and-constraint generation technique is employed to expedite the model-resolving process after the slave problem with integer variables eliminated is equated with the Karush–Kuhn–Tucker conditions. …”
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Optimal Trajectory Tracking for Underactuated Systems via the Takagi–Sugeno Framework: An Autonomous Underwater Vehicle Mission Case Study by Georgios P. Kladis, Lefteris Doitsidis, Nikos C. Tsourveloudis

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A Novel Day Optimal Scheduling Strategy for Integrated Energy System including Electric Vehicle and Multisource Energy Storage by Xiao Ren, Yang Zeng, Zhang Sun, Jun Wang

“…Aiming at problems such as high operating costs, the low utilization efficiency of renewable energy, and the increase in the peak-valley difference in user load caused by disordered charging of electric vehicles (EVs), the operation mode of “setting electricity by heat” or “setting heat by electricity” is adopted in the integrated energy system of intelligent residential areas on the distribution side. …”
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Optimal design of hollow conductor for high‐speed synchronous motor exploiting adaptive‐sampling radial basis function algorithm by Ruiye Li, Peng Cheng, Hai Lan

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Optimization of Tank Cleaning Station Locations and Task Assignments in Inland Waterway Networks: A Multi-Period MIP Approach by Yanmeng Tao, Ying Yang, Haoran Li, Shuaian Wang

“…We formulate the problem as a mixed-integer programming (MIP) model and prove that it can be reformulated into a partially relaxed MIP model, preserving optimality while enhancing computational efficiency. …”
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A new type of sustainable operation method for urban rail transit: Joint optimization of train route planning and timetabling by Guorong Fan, Chao Li, Xinyun Shao, Fangzheng Zhen, Yao Huang

“…Secondly, considering the time-varying passenger flow characteristics and the constraints of operation, a mixed integer nonlinear programming model is established for the joint optimization of train route planning and timetabling to minimize the operating cost and enhance passenger service level. …”
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CBFs-Based Model Predictive Control for Obstacle Avoidance With Tilt Angle Limitation for Ball-Balancing Robots by Minh Duc Pham, Duc Cuong Vu, Thi Thuy Hang Nguyen, Thi-van-Anh Nguyen, Minh Nhat Vu, Tung Lam Nguyen

“…To ensure safe operations, which means that ballbot has to avoid obstacles and maintain tilt angles in a desired range, Nonlinear Model Predictive Control (NMPC) is formulated to predict the position and behavior of the ballbot, followed by the optimization problem assisted by Control Barrier Function (CBF) constraints to drive the ballbot in the safe trajectory. …”
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Location and Size Planning of Charging Parking Lots Based on EV Charging Demand Prediction and Fuzzy Bi-Objective Optimization by Qiong Bao, Minghao Gao, Jianming Chen, Xu Tan

“…Finally, taking the predicted charging demand distribution as an input and the number of CPLs and charging parking spaces as constraints, a bi-objective optimization model for simultaneous location and size planning of CPLs is constructed, and solved using the fuzzy genetic algorithm. …”
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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

“…The algorithm exhibits superior behavior on the IEEE CEC2017 and CEC2022 benchmark functions and demonstrates strong practical utility across four engineering optimization problems with constraints. When applied to multi-degree reduction approximation of Said–Ball curves, the algorithm’s effectiveness is substantiated through four reduction cases, highlighting its superior precision and computational efficiency, thus providing a highly effective and accurate solution for complex curve degree reduction tasks.…”
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Intrusion Detection Using Hybrid Pearson Correlation and GS-PSO Optimized Random Forest Technique for RPL-Based IoT by Wei Yang, Xinlong Wang, Zhiming Zhang, Shaolong Chen, Chengqi Hou, Siwei Luo

“…Second, we propose an efficient routing detection method that accelerates model training speed by using Hybrid Pearson Correlation and GS-PSO(Grid Search-Particle Swarm Optimization) Optimized Random Forest Technique. The Pearson correlation can effectively extract key data features for different routing attacks. …”
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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 experiment demonstrates its excellent performance in high-dimensional decision spaces and multi-objective optimization problems. This work not only provides an innovative multi-objective optimization solution for power dispatch in the spot market environment but also achieves significant improvements in terms of economic efficiency, environmental sustainability, and long-term viability. …”
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Multi-Objective Optimization Design of Low-Frequency Band Gap for Local Resonance Acoustic Metamaterials Based on Genetic Algorithm by Jianjiao Deng, Yunuo Qin, Xi Chen, Yanyong He, Yu Song, Xinpeng Zhang, Wenting Ma, Shoukui Li, Yudong Wu

“…The resulting Pareto-optimal solution set achieves a unit cell mass as low as 26.49 g under the constraint that the band gap deviation does not exceed 2 Hz. …”
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Robust Multi-Stage Planning of Park-Level Integrated Energy System Considering Source-Load Uncertainties by JIANG Xunpu, BAO Zhejing, YU Miao, GUO Chuangxin, GUO Yuanyue, WANG Jian

“…[Methods] First， a box-type uncertainty set is used to model the source-load uncertainty and uncertainty adjustment parameters are introduced to reduce the conservatism of PIES planning and obtain a two-stage robust optimization （TSRO） model. Both discrete and continuous variables are included in the second-stage decision variables of the TSRO model， facilitating directly solving the second-stage problem using Lagrangian duality theory. …”
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Optimal configuration method of fault location monitoring device in low voltage active distribution network based on node participation by CHEN Shaoyu, FENG Yang, ZHENG Zhixiang, XU Yifei, CUI Jianyong, LE Jian

“…The objective function of the optimal monitoring device configuration is built by comprehensively considering the overall participation and the uniformity of the monitoring units, and the economic constraint is considered. …”
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