Search Results - (( using optimization method algorithm ) OR ( using solution using algorithmic ))
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1
Optimal power flow using the Jaya algorithm
Published 2016“…Unlike other population-based optimization methods, no algorithm-particular controlling parameters are required for this algorithm. …”
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2
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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3
Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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4
Solving transcendental equation using genetic algorithm / Masitah Hambari
Published 2004“…Genetic Algorithm is used to find the roots or set of optimal solution that satisfy the equation. …”
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5
Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy
Published 2014“…For this purpose, best solution as fitness function is achieved through CS and WDO algorithm using Kapur’s entropy for optimal multilevel thresholding. …”
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Modification of particle swarm optimization algorithm for optimization of discrete values
Published 2011“…Using this method, the optimization is still done in continuous form, but the solution is generated in discrete form. …”
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Research Reports -
7
Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)
Published 2020“…However, MOPSO algorithm produces a group of non-dominated solutions which make the selection of an “appropriate” Pareto optimal or non-dominated solution more difficult. …”
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8
Network reconfiguration and control for loss reduction using genetic algorithm
Published 2010“…Two methods of load flow solution with different accuracy are employed, i.e., simplified method, which uses the approximation of P and Q at the start of the implemented program, and fast-decoupled method, which gives an exact solution. …”
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9
Optimal Power Flow Solution With Stochastic Renewable Energies Using Nature Inspired Algorithm
Published 2022“…The use of the Moth Flame Optimization (MFO) algorithm to solve optimal power flow as an objective optimization problem in power system operation and control is described in this thesis. …”
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Undergraduates Project Papers -
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Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah
Published 2013“…Optimization of several truss structures (2D and 3D) with discrete variables were carried out using the proposed methods and the results and computational performances were compared with several well-known metaheuristic algorithms. …”
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11
Opposition-based Whale Optimization Algorithm
Published 2018“…The OWOA use the Opposition-based method to enhance Whale Optimization Algorithm (WOA) performance. …”
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Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem
Published 2008“…The computational complexity of most vehicle routing problem and moreover the intricate of stochastic VRP algorithm has made them an important candidate for solution using metaheuristics. …”
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Monograph -
13
Design of radix-4 single path delay fast fourier transform processor with genetic algorithms optimization
Published 2011“…The genetic algorithms is proven to be a very effective method in optimization by using the way imitating natural process of living beings such as crossover, mutation and selection. …”
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14
Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems
Published 2024“…Hence, optimization algorithms, consisting of exact and heuristic methods, are crucial for a myriad of real-world applications. …”
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15
Optimization Of Bar Linkage By Using Genetic Algorithms
Published 2005“…This thesis presents the method of using simple Genetic Algorithms (GAs) in optimizing the size of bar linkage with discrete design variables and continues design variables. …”
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Monograph -
16
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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17
Solution of optimal power flow using non-dominated sorting multi-objective based hybrid firefly and particle swarm optimization algorithm
Published 2020“…Pareto optimal front was obtained by using non-dominated sorting and crowding distance methods. …”
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18
Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems
Published 2015“…This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems
Published 2015“…The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions. …”
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Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training
Published 2020“…Although the gradient information of the commonly used gradient descent training algorithm in WNNs may direct the search to optimal weight solutions that minimize the error function, the learning process is slow due to the complex calculation of the partial derivatives. …”
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