Optimal Control Scheme of Electric Vehicle Charging Using Combined Model of XGBoost and Cumulative Prospect Theory by Youseok Lim, Sungwoo Bae, Jun Moon

“…Using the predicted results, we applied the CPT algorithm to analyze the optimal operational scenarios and assess the expected profit and loss for the power grid. …”
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Optimal Utilization of Ports’ Free-of-Charge Times in One Distribution Center and Multiple Ports Inventory Systems by Zhengyi Li

“…Focusing on stationary and integer-ratio policies, we formulate this inventory management problem as an optimization problem with a convex objective function and a set of integer-ratio constraints and present O(Nlog⁡N) time algorithm to solve the relaxed problem (relaxing the integer-ratio constraints) to optimality, where N is the number of the retailers. …”
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Optimal Fault Tolerant Control of Large-Scale Wind Turbines in the Case of the Pitch Actuator Partial Faults by Younes Ait El Maati, Lhoussain El Bahir

“…The aim is to choose a small fault estimation response time while keeping a weak correlation between the tracking error and the wind turbulence noise. …”
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Comparative Evaluation of Reinforcement Learning Algorithms for Multi-Agent Unmanned Aerial Vehicle Path Planning in 2D and 3D Environments by Mirza Aqib Ali, Adnan Maqsood, Usama Athar, Hasan Raza Khanzada

“…Our findings reveal significant performance differences between the algorithms across multiple dimensions. DDPG consistently demonstrated superior reward optimization and collision avoidance performance, while PPO and MADDPG excelled in the execution time required to reach the goal. …”
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Energy saving and low carbon oriented renovation framework for educational buildings with Tianjin University case study by Xinge Du, Xiang Liu, Feng Gao, Zhihua Zhou

“…This study proposes a data-driven workflow that combines a genetic algorithm with a Bayesian optimization-based XGBoost model to optimize the retrofit design of educational buildings. …”
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Study of the Fatigue Life and Weight Optimization of an Automobile Aluminium Alloy Part under Random Road Excitation by A. Saoudi, M. Bouazara, D. Marceau

“…We present our algorithm developed to optimize the weight of an aluminium alloy sample relative to its fatigue life. …”
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Hierarchical predictive optimal control for range extension of EV with ANN based torque control for IPMSM drives by Lekshmi S, Lal Priya P S

“…The approach involves a hierarchical control scheme that integrates a model predictive controller with a torque vectoring algorithm to optimize torque demand and accurately anticipate road-specific torque requirements. …”
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Two-layer Optimization Scheduling for Off-grid Microgrids Based on Multi-agent Deep Policy Gradient by Huicong FAN, Zhiguo DUAN, Zhiyong CHEN, Shijia ZHU, Hang LIU, Wenxiao LI, Yang YANG

“…The lower-level model optimizes slow-regulating discrete devices based on mixed-integer second-order cone programming, while the upper-level model optimizes fast-regulating continuous devices using a multi-agent deep policy gradient algorithm. …”
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Development and Optimization of a Novel Semi-Submersible Floater for Floating Wind Turbines in the South China Sea by Yiming Zhong, Wenze Liu, Wei Shi, Xin Li, Shuaishuai Wang, Constantine Michailides

“…Using a differential evolution algorithm, the optimization process adjusts column diameter and spacing while considering motion response and steel usage constraints. …”
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Sentence Embedding Generation Framework Based on Kullback–Leibler Divergence Optimization and RoBERTa Knowledge Distillation by Jin Han, Liang Yang

“…First, a sentence embedding generation method based on Kullback–Leibler Divergence (KLD) optimization is proposed, which enhances semantic differentiation between sentence vectors, thereby improving the accuracy of textual similarity computation. …”
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Optimizing HVAC&R System Efficiency and Comfort Levels Using Machine Learning-Based Control Methods by Suroor M. Dawood, Raad Z. Homod, Alireza Hatami

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Determination of future gully erosion risk and its spatially quantitative interpretability of driving factors in regional scale using machine learning algorithms by Xin Liu, Dichen Wang, Mingming Guo, Xingyi Zhang, Zhuoxin Chen, Zhaokai Wan, Jielin Liu

“…This study revealed the future risk of gully erosion under the existing topography, climate, and human activities conditions in the rolling hilly region of northeast China, and explored the optimal algorithm for GERM, which can serve as a reference for the investigation, simulation, and management of gully erosion.…”
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Battery Energy Storage System Optimal Sizing in a Battery Electric Vehicle Fast Charging Infrastructure by Pedro Félix, Luís A. C. Roque, Ismael Miranda, António Gomes

“…This sizing is a result of an optimization based on the interior point algorithm, where the objective is to minimize the costs of maintenance, operation, and installation of a BESS, while properly modelling the different resources such as the BESS, the charging station and EV charging and PV generation. …”
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Optimization of Bandwidth Allocation and UAV Placement in Active RIS-Assisted UAV Communication Networks with Wireless Backhaul by Thi-Thuy-Minh Tran, Binh-Minh Vu, Oh-Soon Shin

“…The resulting optimization problem is highly non-convex, posing significant challenges. …”
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An enhanced moth flame optimization extreme learning machines hybrid model for predicting CO2 emissions by Ahmed Ramdan Almaqtouf Algwil, Wagdi M. S. Khalifa

“…The model integrates the Gaussian mutation and shrink mechanism-based moth flame optimization (GMSMFO) algorithm with an extreme learning machine (ELM). …”
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Dynamic Modeling of a Kaplan Hydroturbine Using Optimal Parametric Tuning and Real Plant Operational Data by Hong Wang, Sunil Subedi, Wenbo Jia

“…To solve this issue, this paper first formulates a six-coefficient Kaplan hydroturbine model and then proposes a parametric optimization tuning framework based on the Nelder–Mead algorithm for adaptive dynamic learning of the six-coefficients so as to build models that describe the turbine. …”
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Exploration design for Q-learning-based adaptive linear quadratic optimal regulators under stochastic disturbances by Vina Putri Virgiani, Shiro Masuda

“…The decaying method gradually reduces the exploration signal over time, enabling effective initial exploration while stabilizing as the system approaches optimal performance. …”
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Balancing conflicting objectives in pre-salt reservoir development: A robust multi-objective optimization framework by Auref Rostamian, Amir Davari Malekabadi, Marx Vladimir De Souda Miranda, Vinicius Edurado Botechia, Denis José Schiozer

“…The study focuses on maximizing expected monetary value (EMV) and the net present value of RM4 considering economic uncertainty (NPVeco of RM4), of the most pessimistic scenario among the RMs. The optimization variables are location, type (injection or production), and number of wells, while the non-dominated sorting genetic algorithm II (NSGA-II) is employed for multi-objective optimization. …”
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Optimizing a Dynamic Vehicle Routing Problem with Deep Reinforcement Learning: Analyzing State-Space Components by Anna Konovalenko, Lars Magnus Hvattum

“…<i>Background:</i> The dynamic vehicle routing problem (DVRP) is a complex optimization problem that is crucial for applications such as last-mile delivery. …”
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Enhanced Particle Swarm Optimization-Based Feeder Reconfiguration Considering Uncertain Large Photovoltaic Powers and Demands by Ying-Yi Hong, Faa-Jeng Lin, Fu-Yuan Hsu

“…Moreover, a two-stage algorithm is developed, in which the uncertain bus loads and PV powers are clustered by fuzzy-c-means to gain representative scenarios; optimal reconfiguration is then achieved by a novel mean-variance-based particle swarm optimization. …”
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