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Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm
Published 2025“…In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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Optimizing decentralized exam timetabling with a discrete whale optimization algorithm
Published 2025“…—In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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Solving the optimal power flow problems using the superiority of feasible solutions-moth flame optimizer
Published 2024“…The main goal of this study is to use a cuttingedge version of recent metaheuristic algorithm, namely Moth-Flame Optimizer (MFO) algorithm for solving the mentioned OPF problems. …”
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Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi
Published 2018“…A Modified Particle Swarm Optimization (MPSO) algorithm, a Genetic Algorithm (GA), a modified fruit fly optimization algorithm (MFOA) and a simulated annealing (SA) algorithm were used to find the optimal solution. …”
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5
A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2025“…The proposed method is a version of the democratic political optimization algorithm in which the search capability of this method to cover the borders of the Pareto frontier is enhanced. …”
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Long-term optimal planning for renewable based distributed generators and battery energy storage systems toward enhancement of green energy penetration
Published 2025“…To solve the optimization planning model, a hybrid optimization algorithm is proposed, combining the non-dominating sorting genetic algorithm (NSGAII) and multi-objective particle swarm optimization (MOPSO). …”
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Optimized fuzzy logic sliding mode control with proportional-integral-derivative for an electrohydraulic actuator system
Published 2023“…Due to the difficulty of concurrent hybrid design, the PSO algorithm was employed to determine the optimal control variables value. …”
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Long-term optimal planning for renewable based distributed generators and plug-in electric vehicles parking lots toward higher penetration of green energy technology
Published 2025“…A hybrid optimization algorithm addresses the proposed objectives, combining the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO) to minimize the three distinct objective functions concurrently. …”
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Modeling of cupping suction system based on system identification method
Published 2022“…The input and output data were used to create this modeling output variable of the cupping suction system is detected by connecting a differential pressure sensor to the cup, while the input variable is determined by the speed of the pump applied in various locations. …”
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Undergraduates Project Papers -
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Operational matrix based on orthogonal polynomials and artificial neural networks methods for solving fractal-fractional differential equations
Published 2024“…Initially, the algorithm utilized a truncated series. The values of the unknown coefficients in this truncated power series were then determined using an optimization technique to minimize the criterion function. …”
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Shunt active power filter using hybrid fuzzy-proportional and crisp-integral control algorithms for total harmonic distortion improvement
Published 2016“…Hence, the use of conventional synchronization algorithms can be neglected.Second, an adaptive Hybrid Fuzzy-Proportional and Crisp-Integral (HFP+CI) current control algorithm is proposed, by using the indirect control strategy together with an integration of Fuzzy-Proportional (Fuzzy-P) and Crisp-Integral (Crisp-I) current controllers. …”
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Application of genetic algorithm methods to optimize flowshop sequencing problem
Published 2008“…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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Undergraduates Project Papers -
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
Published 2018“…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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Application of Hybrid Evolutionary Algorithm and thematic map for rule set generation and visualization of chlorophyta abundance at Putrajaya lake / Lau Chia Fong
Published 2013“…The rules generated by HEA are then integrated with thematic map technique for visualization of the Chlorophyta abundance. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…Several research efforts have been developed to generate optimal operation rules for dam and reservoir systems utilizing different optimization algorithms. …”
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Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China
Published 2024“…In this study, different supervised and unsupervised machine learning algorithms are proposed: artificial neural network (ANN), AutoRegressive Integrated Moving Aveage (ARIMA) and support vector machine (SVM). …”
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Wind farm reactive power optimization by using imperialist competitive algorithm
Published 2013“…In this paper a new evolutionary computing method based on imperialist competitive algorithm (ICA) is used for optimization of the reactive power in a wind farm. …”
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Conference or Workshop Item -
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SA-EVPS ALGORITHM FOR DISCRETE SIZE OPTIMIZATION OF THE 582-BAR SPATIAL TRUSS STRUCTURE
Published 2023“…Nowadays, approximate optimization methods are widely used. This study utilized the Self Adaptive Enhanced Vibrating Particle System (SA-EVPS) algorithm as an approximate optimization method, since the EVPS algorithm requires experimental parameters. …”
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