Multi-Agent Deep Reinforcement Learning for Scheduling of Energy Storage System in Microgrids by Sang-Woo Jung, Yoon-Young An, BeomKyu Suh, YongBeom Park, Jian Kim, Ki-Il Kim

“…To defeat the above issues, in this paper, we propose a new DRL-based scheduling algorithm using a multi-agent proximal policy optimization (MAPPO) framework that is combined with Pareto optimization. …”
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Optimal Skip-Stop Schedule under Mixed Traffic Conditions for Minimizing Travel Time of Passengers by Sun Feng, Zhu Wen-tao, Ye Ying, Wang Dian-hai

“…This paper proposes an optimization model for designing skip-stop service that can minimize the total travel time for passengers. …”
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A Novel NSGA-III-GKM++ Framework for Multi-Objective Cloud Resource Brokerage Optimization by Ahmed Yosreddin Samti, Ines Ben Jaafar, Issam Nouaouri, Patrick Hirsch

“…This paper presents NSGA-III-GKM++, an advanced multi-objective optimization model that integrates the NSGA-III evolutionary algorithm with an enhanced K-means++ clustering technique to improve the convergence speed, solution diversity, and computational efficiency. …”
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A joint optimization method of multi backhaul link selection and power allocation in 6G by Qingyang LI, Xueting LI, Xiaorong ZHU

“…Aiming at the problem of limited single backhaul link capability of base stations in hotspot areas of the 6G system, a joint optimization method was proposed for multi-backhaul link selection and power allocation in an elastic coverage system, so that the data packets can select the appropriate backhaul link and transmission power according to their service characteristics and link conditions.Firstly, the transmission delay of data packets on the small cell sub-queue was analyzed by using queuing theory.Then, the optimization objective was modeled with the maximum delay tolerance elasticity value.Finally, the optimization problem were solved by the Hungarian algorithm and the Lagrangian duality and gradient descent method.The simulation results show that, compared with the traditional algorithm, the algorithm proposed reduces the average delay of URLLC (ultra-reliable and low-latency communication) service data packets and eMBB (enhanced mobile broadband) service data packets by 17% and 14% respectively, and effectively improves the network transmission rate.…”
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Kinematics Analysis and Performance Optimization of Low Coupling PRPaR/2CRR Parallel Mechanism by Zhang Li, Zhu Lei, Xu Dong

“…What's more, a multi-objective optimization design model was established based on the comprehensive performance of the workspace volume, the global dexterity, and the global operability, and the optimal structural parameter size solution was calculated using the NSGA-Ⅱ algorithm. …”
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Energy Interaction and Energy Storage Sharing Optimization Method for Users, Base Stations, and Charging Stations by HU Long, FANG Baling, FAN Feilong, CHEN Dawei, LI Xinxi, ZENG Run

“…Next, incorporating 0-1 integer variables, a solution method utilizes the adaptive differential evolution algorithm combined with the mixed-integer optimization theory. …”
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Flexibility Resource Planning and Stability Optimization Methods for Power Systems with High Penetration of Renewable Energy by Haiteng Han, Xiangchen Jiang, Yang Cao, Xuanyao Luo, Sheng Liu, Bei Yang

“…Furthermore, to mitigate the uncertainty and fault risks associated with extreme weather events, a CVaR-based risk quantification framework is incorporated into a bi-level optimization model, effectively balancing investment costs and operational risks under uncertainty. …”
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Multi-Objective Parameter Optimization of Electro-Hydraulic Energy-Regenerative Suspension Systems for Urban Buses by Zhilin Jin, Xinyu Li, Shilong Cao

“…To streamline multi-objective optimization processes, a particle swarm optimization–back propagation (PSO-BP) neural network surrogate model was developed to approximate the complex co-simulation system. …”
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Numerical Simulation and Optimization of Wind Effects of Porous Parapets on Low-Rise Buildings with Flat Roofs by Ye Qiu, Bingbing San, Youyi Zhao

“…This paper presents a procedure to optimize the porosity of parapets to improve the aerodynamic behavior of low-rise buildings with flat roofs, by coupling an optimization algorithm and computational fluid dynamics (CFD) simulations. …”
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Inter-Satellite Handover Method Based Multi-Objective Optimization in Satellite-Terrestrial Integrated Network by Renpeng LIU, Bo HU, Hequn LI

“…The high-speed motion of low-earth orbit communication satellites results in a highly dynamic network topology, and the spatio-temporal distribution of resources in the satellite-terrestrial integrated network is non-uniform.When multiple users and services switch between satellites, a large number of handover requests are triggered, leading to intensified network resource competition.As a result, the limited satellite resources cannot meet all the handover requests, leading to a significant decrease in handover success rate.In view of the above problem, the multi-objective optimization based satellite handover method was proposed.It introduced the satellite coverage spatio-temporal graph and transforms the dynamic continuous topology into static discrete snapshots, accurately depicted the connections between satellite nodes and users at different times and locations.The multi-objective optimization model was established for satellite handover decisions, and anadaptive accelerated multi-objective evolutionary algorithm(AAMOEA) was proposed to optimized user data rate and network load simultaneously, ensured handover success rate and enhanced network service capability.It built a STIN communication simulation environment and tested the multi user handover performance in a multi satellite overlapping coverage scenario.The results demonstrated that the multi-objective optimization-based satellite handover method achieved an average handover success rate improvement of over 20% compared to benchmark algorithms.…”
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Bi-directional virtual search algorithm for efficient and collision-free path planning in autonomous robots navigating static and dynamic environments by M.D. Yeshwanth Kumar, K. Rajchandar

“…Extensive experiments were conducted across multiple static and dynamic scenarios. The proposed model achieved a path efficiency improvement of 17.9 % and a computational time reduction of 23.4 % compared to traditional A* and Dijkstra’s algorithms. …”
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An Optimal Charging Strategy for PV-Based Battery Swapping Stations in a DC Distribution System by Shengjun Wu, Qingshan Xu, Qun Li, Xiaodong Yuan, Bing Chen

“…Then, a particle swarm optimization (PSO) algorithm is developed to calculate the optimal charging power and to minimize the charging cost for each time slot. …”
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Study on the peak shaving operation of cascade hydropower stations based on the plant-wide optimal curve by Fengshuo Liu, Kui Huang, Xuanyu Shi, Longqing Zhao, Yangxin Yu, Xueshan Ai, Xiang Fu

“…This study proposes a novel method to enhance RES and hydropower utilization through: 1) Establishing a plant-wide optimal output-water level-outflow relationship curve based on the output-head-flow relationship and the flow-head loss and outflow-tailwater level relationship curves for each unit; 2) Developing a short-term peak shaving model for cascaded hydropower stations that incorporates wind and PV power which defines minimum coefficient of variation of residual load as objective functions, and improving discrete differential dynamic programming successive approximation (DDDPSA) method to solve it; 3) Analyzing the peak shaving capacity of the cascade hydropower station by varying water consumption for power generation. …”
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Optimization of Urban Rail Transit Train Stock Utilization under Re-coupling Operation Mode by DENG Chengyuan, LU Jinsheng, ZHU Changfeng, SUN Yuanguang, MA Bin

“…The MTSP ( multiple traveling salesman problem) is introduced to construct an optimized train stock utilization model during the transition period from peak to off-peak passenger flow in urban rail transit. …”
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Robust Sliding Mode Control Based on GA Optimization and CMAC Compensation for Lower Limb Exoskeleton by Yi Long, Zhi-jiang Du, Wei-dong Wang, Wei Dong

“…A genetic algorithm (GA) is utilized to determine the optimal sliding surface and the sliding control law to improve performance of SMC. …”
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Optimized dual NURBS curve interpolation for high-accuracy five-axis CNC path planning by Yi Xu, Mohd Hairi Mohd Zaman, Feng Zhou

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Adaptive RFID Data Scheduling Using Proximal Policy Optimization for Reducing Data Processing Latency by Guowei Guo, Xinsen Yang, Ziwei Liang, Zeli Xi, Ximei Zhan, Peisong Li

“…This paper presents a novel approach for dynamically offloading data using deep reinforcement learning, specifically employing the Proximal Policy Optimization (PPO) algorithm. The proposed method utilizes a central controller equipped with the PPO model to make intelligent, real-time reader selection decisions based on environmental factors such as reader load, tag mobility, and network conditions. …”
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Optimal Scheduling of Biomass-Hybrid Microgrids with Energy Storage: An LSTM-PMOEVO Framework for Uncertain Environments by Zichong Wang, Yingying Zheng

“…Finally, a public dataset was utilized for the experiments to verify the performance of the proposed algorithm. Comparisons and discussions show that the proposed optimization strategies significantly improve the performance of PMOEVO, demonstrating marked advantages over six classical algorithms. …”
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Advancing Arabic Word Embeddings: A Multi-Corpora Approach with Optimized Hyperparameters and Custom Evaluation by Azzah Allahim, Asma Cherif

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Electromagnetic Analysis and Multi-Objective Design Optimization of a WFSM with Hybrid GOES-NOES Core by Kyeong-Tae Yu, Hwi-Rang Ban, Seong-Won Kim, Jun-Beom Park, Jang-Young Choi, Kyung-Hun Shin

“…The optimized WFSM achieved a 13.97% increase in power density and a 1.0% improvement in efficiency compared to the baseline NOES model. …”
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