Cooperative Sleep and Energy-Sharing Strategy for a Heterogeneous 5G Base Station Microgrid System Integrated with Deep Learning and an Improved MOEA/D Algorithm by Ming Yan, Tuanfa Qin, Wenhao Guo, Yongle Hu

“…This paper proposes a cooperative sleep and energy-sharing strategy for heterogeneous 5G base station microgrid (BSMG) systems, utilizing deep learning and an improved multi-objective evolutionary algorithm based on decomposition (MOEA/D). …”
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A Two-Stage Optimization Method for Multi-Runway Departure Sequencing Based on Continuous-Time Markov Chain by Guan Lian, Yingzi Wu, Weizhen Luo, Wenyong Li, Yaping Zhang, Xiaoyue Zhang

“…Then, continuous-time Markov chains (CTMC) were employed to track aircraft state transitions in the taxiway queue, and a nested whale optimization algorithm was proposed to optimize both the pushback sequence and runway resource allocation. …”
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Learning‐based tracking control of AUV: Mixed policy improvement and game‐based disturbance rejection by Jun Ye, Hongbo Gao, Manjiang Hu, Yougang Bian, Qingjia Cui, Xiaohui Qin, Rongjun Ding

“…Moreover, the optimal control problem under disturbances is formulated as a zero‐sum game, and the actor‐critic‐disturbance framework is introduced to approximate the optimal control input, cost function, and disturbance policy, respectively. …”
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Multi-Target Firefighting Task Planning Strategy for Multiple UAVs Under Dynamic Forest Fire Environment by Pei Zhu, Shize Jiang, Jiangao Zhang, Ziheng Xu, Zhi Sun, Quan Shao

“…Results from benchmark tests and case studies indicate that the improved MP–GWO algorithm outperforms the grey wolf optimizer (GWO), pelican optimizer (POA), Harris hawks optimizer (HHO), coyote optimizer (CPO), and particle swarm optimizer (PSO) in solving more complex optimization problems, providing better average results, greater stability, and effectively reducing flight time and path cost. …”
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Harmonized Integration of GWO and J-SLnO for Optimized Asset Management and Predictive Maintenance in Industry 4.0 by A. N. Arularasan, P. Ganeshkumar, Mohammad Alkhatib, Tahani Albalawi

“…The study encompasses the application of two different advanced optimization algorithms on asset management and predictive maintenance in Industry 4.0—Grey Wolf Optimization and Jaya-based Sea Lion Optimization (J-SLnO). …”
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Multi-Objective Optimal Power Flow of Integrated Transmission and Distribution Network Considering Node Carbon Emission Intensity by ZHANG Xianglong, YUAN Zhaoxiang, DONG Shufeng, LIU Ying, XIAO Zhihong, TIAN Yuzhou

“…[Methods] To address these challenges， a collaborative distributed optimal power flow model based on a heterogeneous decomposition algorithm was proposed. …”
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Prediction of Spatiotemporal Distribution of Electric Vehicle Charging Load Based on Multi-Source Information by WANG Qiang, BI Yuhao, GAO Chao, SONG Duoyang

“…Additionally， the Dijkstra algorithm is improved to plan charging paths more effectively by including real-time road condition data. …”
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Optimization of Reverse Logistics Networks for Hazardous Waste Incorporating Health, Safety, and Environmental Management: Insights from Large Cruise Ship Construction by Huilin Li, Jiaqi Yang, Wei Zhang

“…Realistic factors including vehicle load, transport cost, loading time, and risk weight were considered to improve model applicability. …”
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Power capacity enhancement of hydropower plant through the penetration of solar and wind energy by Ahmad Shah Irshad, Ahmad Shah Amin, Amir Mohammad Ilham, M.H. Elkholy, Said Elias, Tomonobu Senjyu

“…A multi-objective genetic algorithm was employed to optimize this integration, addressing objectives such as maximizing power output, improving energy efficiency, and minimizing environmental impact. …”
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Digital Industrial Design Method in Architectural Design by Machine Learning Optimization: Towards Sustainable Construction Practices of Geopolymer Concrete by Xiaoyan Wang, Yantao Zhong, Fei Zhu, Jiandong Huang

“…Consequently, we integrate optimization algorithms (GOA and GWO) with MLP to fine-tune the model’s parameters and improve prediction accuracy. …”
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A Minimized Data Collection Optimization Method for Distribution Networks Considering Multiple-Time and Compressed Candidate Sets by Zhaoxiang YUAN, Zhihong XIAO, Jing WANG, Yanling YU, Yan HUANG, Xingle GAO

“…The minimized data collection technology for distribution networks can optimize the measurement configuration with the minimum economic cost, which plays an important role in improving the system observability. …”
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Prediction of Vehicle Interior Wind Noise Based on Shape Features Using the WOA-Xception Model by Yan Ma, Hongwei Yi, Long Ma, Yuwei Deng, Jifeng Wang, Yudong Wu, Yuming Peng

“…The key hyperparameters of the Xception model are adaptively optimized using the whale optimization algorithm to improve the prediction accuracy and generalization ability of the model. …”
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Optimization Configuration of Electric–Hydrogen Hybrid Energy Storage System Considering Power Grid Voltage Stability by Yunfei Xu, Yiqiong He, Hongyang Liu, Heran Kang, Jie Chen, Wei Yue, Wencong Xiao, Zhenning Pan

“…This model, applied to the IEEE-33 standard test system, utilizes the Multi-Objective Artificial Hummingbird Algorithm (MOAHA) to optimize the capacity and location of the electric–hydrogen hybrid energy storage system. …”
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Prediction and Monitoring Model of Concrete Dam Deformation Based on WOA-RFR by FENG Yu, WU Yunxing, GU Wenjing, PANG Qiong, GU Yanchang, CHEN Siyu

“…The random forest algorithm and whale optimization algorithm were introduced in the construction of the prediction model of concrete dam deformation based on WOA-RFR to improve the prediction accuracy and model performance. …”
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A Hybrid-A* Path Planning Method Based on Equal Step Hierarchical Expansion by CHEN Xinpeng, XU Biao, HU Manjiang, QIN Zhaobo, BIAN Yougang

“…This method can be applied to unstructured road scenes to plan a safe, smooth and driveable path for intelligent vehicles that meets the vehicle kinematic constraints of vehicle operation. First by improving the way of child node development and the reasonable design of the heuristic function and cost function, quick search of guarantee algorithm is a relatively smooth driving path. …”
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Hybrid extreme learning machine for real-time rate of penetration prediction by Abdelhamid Kenioua, Omar Djebili, Ammar Touati Brahim

“…The methodology involves a formation-specific modelling approach, where separate ELM models are trained for each formation using surface drilling parameters such as weight on bit (WOB), rotary speed (RPM), and flow rate. Metaheuristic algorithms optimize the ELM’s weights and biases to improve predictive performance. …”
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Disturbance Observer-Based Bio-Inspired LQR Optimization for DC Motor Speed Control by Mubarak Badamasi Aremu, Mohammed Abdel-Nasser, Nezar M. Alyazidi, and Sami El-Ferik

“…The controller maximizes the capabilities of the integral linear quadratic regulator (ILQR) framework, fine-tuned using state-of-the-art particle swarm optimization (PSO) techniques and a well-defined cost function alongside other bio-inspired algorithms. …”
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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

“…Firstly, to improve the accuracy and stability of wind-photovoltaic power forecasting, a novel multi-objective wind-photovoltaic forecasting model is proposed based on the Laguerre polynomial, pseudo-inverse learning, and hybrid multi-objective Runge-Kutta algorithm (HMORUN). …”
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A Two-echelon Model of Location-routing Problem for Optimizing Relief Operations in Natural Disasters by Hossein Jamali, Mehdi Kabiri Naeini, Zeynab Elahi

“…The goal is to determine the optimal locations for relief bases and routing relief teams to minimize relief time and cost at both levels.  …”
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A Comprehensive Review of Sizing and Energy Management Strategies for Optimal Planning of Microgrids with PV and Other Renewable Integration by Fadi Agha Kassab, Rusber Rodriguez, Berk Celik, Fabrice Locment, Manuela Sechilariu

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