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141
Improved genetic algorithm based on Shapley value for a virtual machine scheduling model in cloud computing
Published 2024-12-01“…IntroductionIn cloud computing, a common idea to reduce operation costs and improve service quality is to study task scheduling algorithms.MethodsTo better allocate virtual machine resources, a virtual machine resource scheduling algorithm, Shapley value method–genetic algorithm (SVM-GA) is proposed. …”
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142
Increasing integration of wind energy through the joint operation of electric vehicles and the grid using the intelligent spider monkey algorithm
Published 2025-04-01“…A significant innovation involves demonstrating that prohibitive constraints on simultaneous charging and discharging can, under specific conditions, be relaxed without compromising system stability, thereby simplifying the optimization process. The optimization problem is formulated as a single objective problem and solved using an improved spider monkey optimization algorithm. …”
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143
Optimization of Wheel Reprofiling Based on the Improved NSGA-II
Published 2020-01-01“…Our study reveals the relationship between the diameter, flange thickness, and their individual attrition rates and proposes a wear model, multiobjective model, and improved NSGA-II. …”
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144
Modelling and optimization of well hole cleaning using artificial intelligence techniques
Published 2025-02-01“…This study aims to improve the accuracy and practicality of hole cleaning assessment by applying Artificial Intelligence (AI) techniques, specifically Artificial Neural Networks (ANN) and Genetic Algorithms (GA), to predict downhole parameters and optimize drilling processes. …”
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145
Optimization of distribution networks using quantum annealing for loss reduction and voltage improvement in electrical vehicle parking management
Published 2025-09-01“…Traditional optimization techniques like Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) often struggle with the nonlinear, high-dimensional nature of EV-grid interaction problems. …”
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146
Edge server deployment decision based on improved NSGA-Ⅱ in the Internet of vehicles edge computing scenario
Published 2024-03-01“…In the context of the Internet of vehicles, the placement and deployment number of edge servers directly affect the efficiency of edge computing.Due to the high cost of deploying a large edge server on a macro base station and a base station, it can be complemented by deploying a small edge server on a micro base station, and the cost reduction needs to be optimized by optimizing the placement of large edge servers.In order to minimize the deployment cost and service delay of the edge server, and maximize the operator’s revenue and server load balance, the edge server placement problem combined with the vehicle networking user application service was modeled as a multi-objective optimization problem and a placement scheme based on improved NSGA-Ⅱ algorithm was proposed.The experimental results show that the proposed scheme can reduce the deployment cost of edge servers by about 44%, the latency by about 14.2%, and improve the revenue of operators by 24.2%, which has good application value.…”
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147
Optimization of Construction Projects Time-Cost-Quality-Environment Trade-off Problem Using Adaptive Selection Slime Mold Algorithm
Published 2024-01-01“…To improve the suggested model's superiority and effectiveness, it is compared to the multiple-target swarm algorithm (MOPSO), multi-objective artificial bee colony (MOABC) and non-dominant sort genetic algorithm (NSGA-II). …”
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148
Cost-Based Optimal Allocation of Shunt Capacitors in Radial Distribution Networks Considering Load Types Using Crow Search Algorithm
Published 2025-01-01“…This study investigates the optimization of capacitor placement and sizing using the Crow Search Algorithm (CSA) to enhance voltage stability, minimize power losses, and reduce operational costs. …”
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149
Operation Optimization Strategy of Commercial Combined Electric Heating System Based on Particle Swarm Optimization Algorithm
Published 2023-02-01“… In order to improve the energy efficiency of the electric heating system, a particle swarm optimization (PSO, Particle Swarm Optimization)-based operation optimization strategy for the direct storage combined electric heating system is proposed.A mathematical model of influencing factors inside and outside the walls of electric heating buildings is established, and the simulink toolbox in matlab is used to build the overall system under the premise of determining the quantity of electric heating.Combining demand response ideas, the objective function is to establish the minimum heating and electricity cost of the user, and different sub-modules are selected to form the control module to achieve simulation verification, and the inverse cosine method is used to update the improved particle swarm algorithm to update the learning factor to solve the set objective function.Finally, through a calculation example of electricity consumption data of an enterprise in Jinan, Shandong, comparing energy consumption and economy can be obtained: the total energy consumption throughout the day is lower than the actual energy consumption, and the electricity bill is reduced by 17.16% compared with the unoptimized time.…”
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150
Presenting a multi-objective decision-making model for cost-time trade-off considering the time value of money and solving it using particle swarm optimization
Published 2024-08-01“…This model assists project managers in gaining better insight into cost-time impacts, optimizing resource allocation, and ultimately improving project performance by reducing delays.…”
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151
Optimal power scheduling in real-time distribution systems using crow search algorithm for enhanced microgrid performance
Published 2024-12-01“…The main contributions of this work include: (1) developing a new meta-heuristic approach for power scheduling in microgrids using the crow search algorithm, (2) achieving optimal power flow and load scheduling to minimize TOC and improve VR, and (3) successfully implementing the proposed methodology in a real-time distribution system using ETAP. …”
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152
Design of improved JAYA algorithm for cigarette finished product logistics delivery
Published 2025-12-01“…In response to these challenges, this study proposes an improved Jaya algorithm that integrates a reverse learning mechanism and a cosine similarity strategy to enhance optimization performance. …”
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153
Development of Hybrid Optimization Model Using Grey-ANFIS-Jaya Algorithm for CNC Drilling of Aluminium Alloy
Published 2024-01-01“…Statistical error analysis is used to estimate the performance of the established optimization model. Based on the investigative outcomes, the best-suited process variable combinations will be used to provide improved and enhanced multiperformance characteristics.…”
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154
Coordinated optimal scheduling of island microgrid for power-hydrogen-carbon integration based on SAO-NSGA-II algorithm
Published 2025-06-01“…Finally, through simulation examples, a comparative analysis of the results before and after the algorithm improvement is performed, validating the feasibility of the proposed improved algorithm and optimal scheduling model. …”
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155
TBESO-BP: an improved regression model for predicting subclinical mastitis
Published 2025-04-01“…The TBESO algorithm notably enhances the efficacy of the BP neural network in regression prediction, ensuring elevated computational efficiency and practicality post-improvement.…”
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156
Insulator Defect Detection Algorithm Based on Improved YOLOv11n
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157
AC Optimal Power Flow Problem Considering Wind Energy by an Improved Particle Swarm Optimization
Published 2024-02-01“…To solve the AC-OPF model, an Improved Particle Swarm Optimization (IPSO) is presented. …”
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The Optimization of Supply–Demand Balance Dispatching and Economic Benefit Improvement in a Multi-Energy Virtual Power Plant within the Jiangxi Power Market
Published 2024-09-01“…The results demonstrate that the proposed scheduling optimization method significantly improves economic benefits while ensuring grid stability. …”
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160
Advanced AI approaches for the modeling and optimization of microgrid energy systems
Published 2025-04-01“…Three AI techniques, Genetic Algorithm (GA), Artificial Bee Colony (ABC), and Ant Colony Optimization (ACO), are employed to optimize the optimal composition of energy sources based on solar energy and wind energy, battery storage, and load profiles. …”
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