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1
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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2
Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah
Published 2013“…In addition, two novel optimization methods are developed and presented which are named the mine blast algorithm (MBA) and the water cycle algorithm (WCA). …”
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Thesis -
3
Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…One of the more recent global optimization tools in the area of discrete optimization is known as the discrete filled function method. …”
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4
Optimal power flow using hybrid firefly and particle swarm optimization algorithm
Published 2020“…The obtained results of the proposed algorithm are compared to simulated results of the original Particle Swarm Optimization (PSO) method and the present state-of-the-art optimization techniques. …”
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5
Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…Artificial Neural Networks (ANN) techniques, mostly Back-Propagation Neural Network (BPNN) algorithm has been used as a tool for recognizing a mapping function among a known set of input and output examples. …”
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6
TUNING A THREE-PHASE SEPARATOR LEVEL CONTROLLER VIA PARTICLE SWARM OPTIMIZATION (PSO) ALGORITHM
Published 2013“…The PSO algorithm mimics the behaviour of bird flocking and fish schooling striving for its global best position. …”
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Final Year Project -
7
Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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8
Performance analysis of clustering based genetic algorithm
Published 2016“…The proposed CGA on which the performance analysis of this paper is based involve the use of two centroids based clustering technique as a new method of chromosomes selection at the reproduction stage in a typical Genetic Algorithm. …”
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Proceeding Paper -
9
Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…Realcoded genetic algorithm (RCGA) as a stochastic global search method was applied for optimization. …”
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10
Network reconfiguration and control for loss reduction using genetic algorithm
Published 2010“…Tests results show that Genetic Algorithm is a suitable algorithm as it is an optimization technique with, high accuracy, and it avoids local minimum by searching in several regions to arrive to the global optimum solution. …”
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11
Optimized processing of satellite signal via evolutionary search algorithm
Published 2000“…A combination of three methods, namely optimization, global random search and ambiguity function mapping has produced an efficient and robust mitigation technique. …”
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African Buffalo Optimization
Published 2016“…Experimental results obtained from applying the novel ABO to solve a number of benchmark global optimization test functions as well as some symmetric and asymmetric Traveling Salesman’s Problems when compared to the results obtained from using other popular optimization methods show that the African Buffalo Optimization is a worthy addition to the growing number of swarm intelligence optimization techniques. …”
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Tuning A Three-Phase Separator Level Controller via Particle Swarm OptimizationAlgorithm
Published 2019“…The PSO algorithm mimics the behaviour of bird flocking and fish schooling striving for its global best position. …”
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Conference or Workshop Item -
14
Implementation of simulated annealing for two variables non-linear function
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Working Paper -
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
Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2023“…The Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. …”
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Combined heat and power (CHP) economic dispatch solved using Lagrangian relaxation with surrogate subgradient multiplier updates
Published 2023“…Flexibility for the choice of algorithm is given at the lower levels optimization techniques with the condition that the algorithm is able to improve its search at each iteration. …”
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Enhancing three variants of harmony search algorithm for continuous optimization problems
Published 2021“…Meta-heuristic algorithms are well-known optimization methods, for solving real-world optimization problems. …”
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Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification
Published 2015“…The proposed CSERN and CSBPERN algorithms are compared with artificial bee colony using BP algorithm and other hybrid variants algorithms. …”
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Enhancing performance of global path planning for mobile robot through Alpha–Beta Guided Particle Swarm Optimization (ABGPSO) algorithm
Published 2025“…The results reveal that our proposed method reduces the mobile robot's travel time by up to 69%, 67%, 72%, and 79% compared to these algorithms, while consistently achieving optimal path lengths. …”
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