OPTIMAL DISTRIBUTION NETWORK RECONFIGURATION FOR LOSS MINIMIZATION AND VOLTAGE PROFILE IMPROVEMENT BASED ON ARTIFICIAL INTELLIGENCE by Omar Muhammed Neda

“…The original version of the Dolphin Echolocation Optimization (DEO) algorithm is designed for solving continuous optimization issues only. …”
Get full text

A Multi-Objective PSO-GWO Approach for Smart Grid Reconfiguration with Renewable Energy and Electric Vehicles by Tung Linh Nguyen, Quynh Anh Nguyen

“…While the Particle Swarm Optimization algorithm is renowned for its rapid convergence and effective exploitation of solution spaces, its capacity to thoroughly explore complex search domains remains limited, particularly in multifaceted optimization challenges. …”
Get full text

GENERATING OF OPTIMAL QUANTIZATION LEVELS OF CONTROL CURRENTS FOR LINEAR STEPPING DRIVES OF PRECISION MOTION SYSTEMS by I. V. Dainiak, V. P. Oger, D. S. Tsitko, D. G. Begun

“…An algorithm for determination of optimal quantization levels of control currents of drive's phases has been developed in the paper; it minimizes an error of positioning that forms correction files for application of a control system in the software. …”
Get full text

The optimization of treatment of patients with community-acquired pneumonia with high cardiovascular risk (case from practice). by V. F. Orlovskii, A. V. Zharkova, S. Ya. Udovichenko

Get full text

Multi‐objective multi‐period optimal site and size of distributed generation along with network reconfiguration by Ghulam Abbas, Zhi Wu, Aamir Ali

“…To address the pointed‐out challenge of multiperiod optimal DG allocation and reconfiguration while simultaneously decreasing the cost of energy supplied, the cost of energy lost, and the voltage deviation, a novel Multi‐objective Bidirectional co‐evolutionary algorithm (BiCo) is implemented. …”
Get full text

Comprehensive Evaluation Method of Teaching Effect Based on Particle Swarm Optimization Neural Network Model by Heng Cao, Qianhui Gao

“…This paper studies the optimization algorithm and optimization system, it not only makes the algorithm involve basic mathematical operations, and the computer support required for the data processing process is not high, but it also improves the evaluation of the degree of optimization. …”
Get full text

Modeling and Optimization of the Multiobjective Stochastic Joint Replenishment and Delivery Problem under Supply Chain Environment by Lin Wang, Hui Qu, Shan Liu, Cai-xia Dun

“…Secondly, two approaches are designed to handle this complex multi-objective optimization problem. Linear programming (LP) approach converts the multi-objective to single objective, while a multi-objective evolution algorithm (MOEA) solves a multi-objective problem directly. …”
Get full text

A Hierarchical Control Algorithm for a Pursuit–Evasion Game Based on Fuzzy Actor–Critic Learning and Model Predictive Control by Penglin Hu, Chunhui Zhao, Quan Pan

“…FACL is used for perception, decision-making, and predicting the trajectories of agents, while MPC is utilized to address the flight control and target optimization of quadrotors. …”
Get full text

Research on the optimization method of emergency material post transportation model based on bi-level programming by Haixia ZHOU, Yurong MEI, Furu LYU, Zhixin SUN

“…Emergency logistics is a special logistics activity that protects the need of personnel,materials and funds in the event of a major emergency.In the post transportation model of emergency supplies,how to quickly and accurately deliver a large amount of rescue materials to the place of need is a huge challenge to emergency logistics.The logistics cost and the logistics time in the entire logistics process could be minimized by the bi-level planning method while meeting the demand for emergency supplies at the demand point.The bi-level programming model was constructed with the minimum logistics cost of the upper layer and the shortest logistics time of the bottom layer as the goal,and a hybrid tabu search genetic algorithm (HTSGA) was designed to solve the model,which solved the problem of emergency logistics transportation route optimization after the disaster.Finally,the experimental result comparison verified the effectiveness of the model and algorithm.…”
Get full text

Swarm based Heuristic Optimization of the Recurrent Customers and Standby Server Under General Retrial Times by N. Micheal Mathavavisakan, K. Indhira, Aliakbar Montazer Haghighi

“…The results revealed that these algorithms successfully minimized operational costs while maintaining optimal system efficiency. …”
Get full text

Optimizing low-power, anti-interference routing with IRS through spatiotemporal reinforcement and federated learning by Chengfu Fan, Shoujiu Xiong, Fei Zhou

“…These findings highlight the algorithm’s ability to balance signal optimization with energy efficiency. …”
Get full text

Maritime Port Freight Flow Optimization with Underground Container Logistics Systems Under Demand Uncertainty by Miaomiao Sun, Chengji Liang, Yu Wang, Salvatore Antonio Biancardo

“…A stochastic optimization model is developed, incorporating transportation, environmental, carbon tax and subsidy, and congestion costs while satisfying various constraints, such as capacity limits, time constraints, and low-carbon transport requirements. …”
Get full text

Optimization of ore production scheduling strategy using NSGA-II-GRA in open-pit mining by ZhongQiang Chen, PingCheng Song, RunHan Liu, Qi Wang, YuMeng Shen

“…Abstract To address the challenges posed by ore grade fluctuations, extraction cost variations, and market price instability in open-pit ore production strategies, an optimization model integrating a solution algorithm integrating dynamic simulation is proposed. …”
Get full text

Performance optimization of active RIS-assisted near-shore dual-function radar communicaiton system by XU Miao, YUE Dianwu, SUN Yu, WU Xiangkai, YUAN Meng

“…Simulation results show that the proposed algorithm has good convergence properties. Compared with the DFRC system assisted by a passive reflective intelligent surface (RIS), the ARIS-assisted coastal DFRC system can significantly improve the weighted sum rate of maritime users while maintaining the same detection power.…”
Get full text

Research on Feature Extraction Method and Process Optimization of Rolling Bearing Faults Based on Electrostatic Monitoring by Ruochen Liu, Han Yin, Jianzhong Sun, Lanchun Zhang

Get full text

Coverage optimization and node minimization in WSNs: an enhanced hybrid PSO approach with spatial position encoding by Yinghua Tong, Lianhai Lin, Liqin Tian, Zhigang Wang, Wenxing Wu, Junyi Wu

“…This paper presents an enhanced hybrid particle swarm optimization (EHPSO) algorithm that incorporates a spatial position encoding (SPE) strategy to optimize coverage while dynamically adjusting the number of sensors deployed in WSNs. …”
Get full text

Optimal Configuration of Hybrid Energy Storage Capacity for Wind Farms Considering Carbon Trading Revenue by Chongde CHEN, Qiang GUO, Ziqiu SONG, Yang HU

“…In view of the cost of initial investment and replacement of energy storage as well as the revenue from electricity sales and carbon trading, an optimal configuration model of hybrid energy storage capacity for wind farms was established and solved by an adaptive chaotic particle swarm optimization algorithm. …”
Get full text

Information-Driven Model Predictive Control With Adaptive Partitioning for Energy Optimization in Automated Electric Vehicles by Shahriar Shahram, Yaser P. Fallah

“…These convex models are integrated into the MPC to compute optimal control inputs that minimize energy consumption while satisfying vehicle dynamics and constraints. …”
Get full text

Self-Organized Connectivity Control and Optimization Subjected to Dispersion of Mobile Ad Hoc Sensor Networks by Zhenqiang Mi, Yang Yang, Hao Ding

Get full text

Replica exchange enhanced adaptively weighted stochastic gradient Langevin dynamics for Bayesian sampling and optimization by Zhenqing Wu, Wenwu Gong, Ziying Yu, Liuxin Zhu, Lili Yang

“…By merging the 1/k-ensemble and replica exchange methods, this algorithm effectively escapes local traps in Monte Carlo simulation and non-convex optimization. …”
Get full text