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Hybrid harmony search algorithm for continuous optimization problems
Published 2020“…Taken together, the proposed hybrid algorithm, called IHS-GWO, aims to address continuous optimization problems. …”
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An improved artificial bee colony algorithm based on mean best-guided approach for continuous optimization problems and real brain MRI images segmentation
Published 2024Subjects: “…Optimization algorithms…”
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Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems
Published 2024“…Hence, in this project, the exploitation of the original DA is improved by using the stochastic hill climbing algorithm as a local search technique. The optimized continuous DA is applied for the training of Artificial Neural Networks (ANNs) so as to determine the optimal connection weights and biases for the network. …”
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Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems
Published 2018“…The SKF algorithm only capable to solve numerical optimization problems which involve continuous search space. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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Hybridizing Invasive Weed Optimization with Firefly Algorithm for Unconstrained and Constrained Optimization Problems
Published 2017“…The invasive weed optimization (IWO) algorithm, on the other hand, is effective in accurate global search, but not in local search. …”
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Performance evaluation of Black Hole Algorithm, Gravitational Search Algorithm and Particle Swarm Optimization
Published 2015“…In this paper, performance of BH algorithm will be analyzed and reviewed for continuous search space using CEC2014 benchmark dataset against Gravitational Search Algorithm (GSA) and Particle Swarm Optimization (PSO). …”
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DNA Words Based on an Enhanced Algorithm of Multi-objective Particle Swarm Optimization in a Continuous Search Space
Published 2011“…In this paper, particle swarm optimization algorithm in a continuous search space is implemented to generate a set of DNA words. …”
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Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems
Published 2018“…The SKF algorithm only capable to solve numerical optimization problems which involve continuous search space. …”
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Data fitting by G1 rational cubic Be´zier curves using harmony search
Published 2015“…HS is a derivative-free real parameter optimization algorithm, and draws an inspiration from the musical improvisation process of searching for a perfect state of harmony. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…Analysis and comparison of the obtained results indicate the efficiency and competitiveness of the proposed algorithm in addressing unconstrained continuous optimization tasks.…”
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Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling
Published 2022“…In order to accomplish better performance by improving the search quality and efficiency of the discrete MOPSO, this research proposes a hybrid with the Diversification Generation Method in Scatter Search, the non-dominated sorting mechanism in non-dominated sorting Genetic Algorithm II (NSGA-II) and the local search mechanism in Tabu Search. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters
Published 2013“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous in nature, the values wil have to be discretized.The discretization process will result in loss of some information and, hence, affects the classification accuracy and seeks time.This paper presents an algorithm to optimize Support Vector Machine parameters using Incremental continuous Ant Colony Optimization without the need to discretize continuous values.Eight datasets from UCI were used to evaluate the performance of the proposed algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.Experimental results of the proposed algorithm also show promising performance in terms of classification accuracy and size of features subset.…”
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A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer
Published 2019“…Metaheuristic algorithms have received much attention recently for solving different optimization and engineering problems. …”
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A New Hybrid Simulated Kalman Filter and Particle Swarm Optimization for Continuous Numerical Optimization Problems
Published 2015“…The performance of the proposed hybrid SKF-PSO algorithm (SKF-PSO) is compared against SKF and PSO using CEC2014 benchmark dataset for continuous numerical optimization problems. …”
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Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…We model the recently established feature selection method, competitive binary grey wolf optimizer (CBGWO), into a continuous version (CGWO), which enables it to perform the search on continuous search space. …”
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Optimizing support vector machine parameters using continuous ant colony optimization
Published 2012“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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Crossover-first differential evolution for improved global optimization in non-uniform search landscapes
Published 2015“…In order to test this simple and straightforward modification to the DE algorithm, we compared its performance against the original DE algorithm using the CEC2005 global optimization’s set of 25 continuous optimization test problems. …”
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