Search Results - (( using optimization means algorithm ) OR ( using solution using algorithm ))
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Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
Published 2023“…The statistical tools (Absolute Mean Error & Fried Man) are used to rank the performance of all algorithms. …”
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An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem
Published 2021“…It is noticed that the AdamSE algorithm has the smallest iteration number. ,e results show that the rate of convergence of the Adam algorithm is significantly enhanced by using the AdamSE algorithm. …”
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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…However, the PSO algorithm produces a group of non-dominated solutions which makes the choice of a “suitable” Pareto optimal or non-dominated solution more difficult. …”
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4
Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…In the first sub-algorithm, the state mean propagation removes the Gaussian white noise to obtain the expected solution. …”
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The effect of job satisfaction on the relationship between organizational culture and organizational performance
Published 2023“…The statistical tools (Absolute Mean Error & Fried Man) are used to rank the performance of all algorithms. …”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
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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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Data clustering using the bees algorithm
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Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems
Published 2021“…To reduce the optimization time of the tours created by the artificial bee colony algorithm, the fixed-radius near neighbor 2-opt algorithm was used as well. …”
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Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems
Published 2014“…The integrated algorithms use two genetic representations for the individual solution entire sub-chromosomes. …”
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Document clustering based on firefly algorithm
Published 2015“…Document clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters.Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization.This study explores the adaptation of another swarm algorithm which is the Firefly Algorithm (FA) in text clustering.We present two variants of FA; Weight- based Firefly Algorithm (WFA) and Weight-based Firefly Algorithm II (WFAII).The difference between the two algorithms is that the WFAII, includes a more restricted condition in determining members of a cluster.The proposed FA methods are later evaluated using the 20Newsgroups dataset.Experimental results on the quality of clustering between the two FA variants are presented and are later compared against the one produced by particle swarm optimization, K-means and the hybrid of FA and -K-means. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…In general, genetic based clustering algorithms showed the ability to reach near global optimal solution. …”
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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ENGINEERING DESIGN WITH PSO ALGORITHM
Published 2019“…This dissertation will demonstrate the ability of PSO Algorithm in improving design areas by the use of recommendation system that helps engineering designers to visualise an optimal design.…”
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm
Published 2024“…This proposed algorithm produced solutions with superior accuracy and consistency compared to various established metaheuristic strategies, including particle swarm optimizer, grey wolf optimizer, multi-verse optimizer, AOA, and a hybrid optimizer (average multi-verse optimizer-sine-cosine algorithm).…”
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Approximate maximum clique algorithm (AMCA): A clever technique for solving the maximum clique problem through near optimal algorithm for minimum vertex cover problem
Published 2018“…The only way left is to use the approximation algorithm of Minimum Vertex Cover (MVC) for the solution of the Maximum Clique (MC) problem. …”
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