Search Results - (( using optimization method algorithm ) OR ( variable localization based algorithm ))
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Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly
Published 2023“…The first method is greedy heuristic method. Greedy heuristics is a type of optimization algorithm that makes decisions based on locally optimal solutions. …”
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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…These problems are known as discrete-valued optimal control problems. Most practical discrete-valued optimal control problems have multiple local minima and thus require global optimization methods to generate practically useful solutions. …”
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3
Multi-Objective Multi-Exemplar Particle Swarm Optimization Algorithm with Local Awareness
Published 2024“…One of these MOO algorithms Multi-Objective Particle Swarm Optimization (MOPSO) extends it to handle problems with multiple objectives simultaneously, but like many swarm-based algorithms, MOPSO can suffer from premature convergence or local optima solutions. …”
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Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis
Published 2014“…The Particle Swarm Optimization (PSO) Algorithm is a popular optimization method that is widely used in various applications, due to its simplicity and capability in obtaining optimal results. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…To summarise, metaheuristic algorithms can give a superior optimization approach than the traditional artificial neural network method, providing the computing time is within an acceptable range. …”
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6
Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm
Published 2025“…This paper presents a novel discrete Whale Optimization Algorithm approach, integrating the strengths of population-based and local-search algorithms for addressing the examination timetabling problem, a significant challenge many educational institutions face. …”
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Optimizing decentralized exam timetabling with a discrete whale optimization algorithm
Published 2025“…This paper presents a novel discrete Whale Optimization Algorithm approach, integrating the strengths of population-based and local-search algorithms for addressing the examination timetabling problem, a significant challenge many educational institutions face. …”
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…It addresses the limitations of the original Archimedes optimization algorithm (AOA) through two key modifications: rebalancing the exploration and exploitation phases and mitigating local optima trapping issues. …”
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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10
Optimizing lossless compression by normalized data length in Huffman Algorithm
Published 2022“…The proposed new algorithm has more optimal CR than the various variants of the Huffman-based lossless application. …”
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11
A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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13
Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…The data vectors are assigned to the closest cluster and correspondingly to the set, which contains this cluster and an algorithm based on a derivative-free method is applied to the solution of this problem. …”
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14
Using Pattern Search Methods for Minimizing Clustering Problems
Published 2010“…Recently, the problem of cluster analysis is formulated as a problem of nonsmooth, nonconvex optimization,and an algorithm for solving the cluster analysis problem based on nonsmooth optimization techniques is developed. …”
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15
Crossover and mutation operators of real coded genetic algorithms for global optimization problems
Published 2016“…The rationale behind developing algorithms using real encoding of chromosome representations is the limitations of binary encoding. …”
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16
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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The use of heuristic ordering and particle swarm optimization for nurse scheduling problem
Published 2017“…The capability of PSO algorithm is enhanced by emphasizing the use of information on the constraints and heuristic ordering for searching optimal solution in both the feasible and infeasible solution spaces. …”
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19
Use of AR Block Processing for Estimating the State Variables of Power System
Published 2008“…This problem is solved by introducing signal-processing technique for identifying and changing the measurement weights of the bad measurements if the related measurement is assigned with high weight factors. Samples of the local utility network for 103-bus parameter are collected and simulated using Burg and Modified Covariance algorithm to estimate the state variables. …”
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New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams
Published 2022“…Only one dynamic variable is used as a tuning parameter reducing the complexity of the algorithm. …”
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