Search Results - (( simulation optimization based algorithm ) OR ( using variational study algorithm ))
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PARTICLE SWARM OPTIMIZATION MAXIMUM POWER POINT TRACKING FOR PARTIALLY SHADED SOLAR PV
Published 2023“…The energy conversion system and PSO algorithm were simulated in MATLAB/Simulink. The simulation results demonstrate the viability of the developed PSO method because the PSO-based MPPT controller can maximize power from the solar panel under a solar irradiation variation. …”
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Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm
Published 2022“…Nevertheless, many existing optimization tools for tuning the FOPID controller, which are based on multi-agent based optimization, require large number of function evaluation in their algorithm that could lead to high computational burden. …”
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Assessment of energy storage and renewable energy sources-based two-area microgrid system using optimized fractional order controllers
Published 2024“…Simulation results reveal that the AOA-based CFOID-FOPIDN outperforms other existing algorithms, such as particle swarm optimization (PSO), bat algorithm (BAT), moth flame optimization (MFO), and whale optimization algorithm (WOA). …”
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Power system stabilizer optimization using BBO algorithm for a better damping of rotor oscillations owing to small disturbances
Published 2023“…A relative comparative study is conducted between the algorithms such as BBO, particle swarm optimization (PSO) and the adaptation law based PSS on SMIB. …”
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…In this study, the performance of these three algorithms in obtaining the optimal blade design based on the �436�45D are investigated and compared. …”
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Optimizing crystal size distribution based on different cooling strategies in batch crystallization process
Published 2024“…Based on the simulation results, optimization IV, which maximizes CSD, performs best with a large mean crystal size of 490 µm. …”
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Design and implementation of an optimal fuzzy logic controller using genetic algorithm
Published 2008“…Said approach was first simulated using MATLAB/SIMULINK using the techniques of Proportional Derivative Fuzzy Logic Controller (PD-FLC) whose membership function, fuzzy logic rules and scaling gains were optimized by the genetic algorithm technique. …”
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Efficiency improvement of a standalone photovoltaic system using fuzzy-based maximum power point tracking algorithm
Published 2016“…The MPPT algorithms imply the optimal duty ratio to drive the matching converter for optimal maximum power tracking. …”
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Techno-economic optimization and modelling of grid-connected photovoltaic and battery energy storage system
Published 2023“…Optimization was performed via MATLAB using particle swarm optimization (PSO) and Genetic Algorithms (GA) techniques. …”
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Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method
Published 2016“…Since the proposed models (like similar models in the literature) are likely to fall into local optimum points, a Branch and Bound based heuristic, a hybrid Simulated Annealing and Genetic algorithm, a hybrid Tabu search and Simulated Annealing, a hybrid Genetic algorithm and Simulated Annealing, a hybrid Ant Colony Optimization and Simulated Annealing and a hybrid Multi-layer Perceptron and Simulated Annealing algorithms are developed. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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Performance evaluation of heuristic methods in solving symmetric travelling salesman problems
Published 2016“…The purpose of this study is to carry out a comparative evaluation study on Simulated Annealing (SA) and several variation of Tabu Search (TS).Materials and Method: This study considers four heuristic methods, i.e., Simulated Annealing (SA), conventional Tabu Search (TS), Improved Tabu Search (ITS) and modified Reactive Tabu Search (RTS) to solve symmetric TSPs.The algorithms were tested on five chosen benchmark problems. …”
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Evaluation of optimal cooling control for seeded batch crystallization inclusive dissolution with uncertainties
Published 2020“…Therefore the objective of this study is to develop the optimal cooling control inclusive dissolution phenomena for batch seeded crystallization using potassium nitrate crystallization as a case study. …”
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Enhanced stability and performance of the tidal energy conversion system using adaptive optimum relation-based MPPT algorithms
Published 2025“…The A-ORB algorithm integrates the optimum relation-based (ORB) approach with Hill Climb Search (HCS), along with an adaptive gain adjustment mechanism that dynamically tunes the parameter K based on power variation (ΔP). …”
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Maximum Demand Reduction (MDRed) modelling using MATLAB Stateflow
Published 2024“…Based on renewable energy case studies, the MDRed (Maximum Demand Reduction) Model is created as an optimization apparatus for the solar PV-battery system. …”
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Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods
Published 2017“…The advantage of using these algorithms is obvious as they would speed up the computation to obtain higher accuracy with less computation effort. …”
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Capacity Planning For Mixed-Load Tester Under Demand And Testing Time Uncertainty
Published 2018“…Currently,the company’s issue is low tester utilization of about 71%,well below the target of 96%.The objective of this research is to improve tester utilization while achieving the production target under uncertain demand and testing time and also to determine the break-even point on the testers required.A novel approach of integrating a mathematical model,robust optimization model,genetic algorithm,simulation model and cost–volume –profit analysis was developed.Firstly,a mathematical model of mixed-load tester was formulated.Next,a set of discrete scenarios was proposed to address uncertain demand and testing time.A robust optimization and genetic algorithm model was developed to optimize the number of testers under the described uncertainties.Next,these scenarios were simulated using the Pro Model simulation software to validate the proposed models and to evaluate throughput and tester utilization.Finally,the cost–volume–profit analysis was performed for scenarios that require additional testers at various levels of uncertainties.The results showed that the proposed solution improved tester utilization by 25% compared to the current system.This research has contribution by developing novel hybrid methodology and able to provide useful insights to assist company’s managers to plan and allocate resources according to variations in customers’ demands and testing time.…”
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Modeling of CO emissions from traffic vehicles using artificial neural networks
Published 2019“…The hybrid model was developed based on the integration of GIS and the optimized Artificial Neural Network algorithm that combined with the Correlation based Feature Selection (CFS) algorithm to predict the daily vehicular CO emissions and generate prediction maps at a microscale level in a small urban area by using a field survey and open source data, which are the main contributions to this paper. …”
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