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78 results for “Global Optimization”
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Research ArticleOpen accessPhrase in the titleVariable Neighborhood Simplex Search Methods for Global Optimization ModelsPongchanun LuangpaiboonProblem statement: Many optimization problems of practical interest are encountered in various fields of chemical, engineering and management sciences. They are computationally intractable. Therefore, a practical algorithm for solving such problems is to employ approximation algorithms that can find nearly optimums within a reasonable amount of computational time. Approach: In this study the hybrid methods combining the Variable Neighborhood Search … …Journal of Computer Science, Vol. 8, Issue 4 · 15 Feb 2012 · 6,510 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleParameter Settings for New Generational Genetic Algorithms for Solving Global Optimization ProblemsSiew Mooi Lim, Md. Nasir Sulaiman, Norwati Mustapha, Abu Bakar Md. SultanThis study operates within experimental design with two main tools of Taguchi method namely orthogonal array and signal to noise ratio to discover the optimal parameter settings for newly proposed generational genetic algorithms; they are Laplace Crossover-Scale Truncated Pareto Mutation (LX-STPM) and Rayleigh Crossover-Scale Truncated Pareto Mutation (RX-STPM). It concluded that GA parameter settings are algorithms and problems dependent. …Journal of Computer Science, Vol. 11, Issue 11 · 7 Jan 2016 · 6,404 accessesView PDFCite
Research ArticleOpen accessIn the keywordsNatural Reforestation Optimization (NRO): A Novel Optimization Algorithm Inspired by the Reforestation ProcessFernando L. Rodríguez-Gallegos, César A. Rodríguez-Gallegos, Andrés A. Rodríguez-Gallegos, Carlos D. Rodríguez-GallegosThis paper proposes a new meta-heuristic-based optimization algorithm for single-objective problems. The algorithm is called Natural Reforestation Optimization (NRO) and is inspired by the process in which natural reforestation takes place. The features of this algorithm (such as the distribution of the initial population, the exploration and exploitation mechanisms, the interactions between the particles, the stopping criteria, among others) are … …Journal of Computer Science, Vol. 16, Issue 8 · 2 Sep 2020 · 6,655 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Robust Modification of Hestenes–Stiefel Conjugate Gradient Method with Strong Wolfe Line SearchAwad Abdelrahman, Osman O.O. Yousif, Khalid I. OsmanNonlinear Conjugate Gradient (CG) methods are extensively used for solving large-scale unconstrained optimization problems. Numerous of studies constructed scales and modifications have been conducted recently to improve (CG) methods. In this paper, a simple modified by its conjugate gradient method was proposed. In addition to, established global convergence property and sufficient descent condition, under Strong Wolfe line search. Numerical result … …Journal of Mathematics and Statistics, Vol. 16, Issue 1 · 14 May 2020 · 6,743 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEFFECTIVENESS OF SECOND BEST PARTICLE INFORMATION FOR PARTICLE SWARM OPTIMIZATIONEisuke Kita, Young-Bin ShinParticle Swarm Optimization (PSO) represents the potential solutions of the optimization problem as the particles and then, the particles move in order to find the better solution. The particle positions are updated from the personal best and the global best particle positions which have been ever found. This research focuses on the use of the second personal best and the … …Journal of Computer Science, Vol. 9, Issue 11 · 23 Sep 2013 · 6,576 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHybrid Exponential Particle Swarm Optimization K-Means Algorithm for Efficient Image SegmentationK. M. Murugesan, S. PalaniswamiThe introduction of unsupervised learning techniques like K-means inside the domain of Image Processing plays a vital role in Image Segmentation. The hybridization of this Algorithm by using Swarm Intelligent techniques further more improves the efficiency. Various works on hybridization of Particle Swarm Optimization (PSO) with K-means have been proposed and are found to be efficient in Image Segmentation. However, … …Journal of Computer Science, Vol. 8, Issue 11 · 25 Oct 2012 · 7,141 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Optimal Approach for Medical Image AnalysisJ. Umamaheswari, G. RadhamaniProblem statement: Image segmentation is the process that subdivides an image into its constituent parts and extracts the objects. It is one of the most critical tasks in automatic image analysis because the subdivided results will affect all the subsequent processes of image analysis, such as object representation and description, feature measurement and even the following higher level tasks such … …Current Research in Bioinformatics, Vol. 1, Issue 1 · 6 Jun 2012 · 9,513 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHEURISTIC DISCRETIZATION METHOD FOR BAYESIAN NETWORKSMariana D.C. Lima, Silvia M. Nassar, Pedro Ivo R.B.G. Rodrigues et al.Bayesian Network (BN) is a classification technique widely used in Artificial Intelligence. Its structure is a Direct Acyclic Graph (DAG) used to model the association of categorical variables. However, in cases where the variables are numerical, a previous discretization is necessary. Discretization methods are usually based on a statistical approach using the data distribution, such as division by quartiles. In … …Journal of Computer Science, Vol. 10, Issue 5 · 18 Jan 2014 · 7,054 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementing a Hybrid VMD–BiTCN–BiGRU Architecture With Intelligent Optimization for Agricultural Commodity Price Prognostication in Gujarat MarketsJignesh Hirapara, Ratnesh Kumar Namdeo, Ankit Kumar Dubey et al.In the agricultural sector, the prices of pulses require adequate forecasting to plan farming activities, store and market, and guide policy-making. However, the pulse price series is highly volatile, seasonal, nonstationary, and nonlinear, and thus conventional linear time series models are not necessarily very effective. In the suggested framework, the raw price data series is decomposed using Variational Mode Decomposition … …Journal of Computer Science, Vol. 22, Issue 7 · 1 Aug 2026 · 1,021 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized Cloud Load Balancing Using Deep Q-Learning With Inverted S-Shaped Hierarchical Reverse Superb Fairy-Wren OptimizationB. R. Yogeetha, S. P. AnandarajCloud computing offers a scalable and cost-effective platform by providing on-demand access to shared computational resources. However, effective load balancing is essential to maintain optimal performance and maximize resource utilization for ensuring even distribution of network traffic across servers, preventing overload, improving response time and enhancing the system reliability. This manuscript proposes the Deep Q-Network with Inverted S-shaped Hierarchical Reverse … …Journal of Computer Science, Vol. 22, Issue 6 · 4 Jun 2026 · 1,497 accessesView PDFCite