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A method for the minimum coloring problem using genetic algorithms
Published 2006“…This paper presents a method to solve the graph coloring problem for arbitrary graphs using genetic algorithms. …”
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A reduced model for phase-change problems with radiation using simplified PN approximations
Published 2025“…Radiative heat transfer in phase-change media is of great interest in many thermal applications in sciences and engineering involving internal melting or solidification. In these problems at high temperature, a mathematical model used to describe the heat transfer and phase change should also include equations accounting for thermal radiation. …”
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A Neural Networks Algorithm for the Minimum Colouring Problem Using FPGAs†
Published 2010“…This paper presents a hardware implementation to solve the graph colouring problem (chromatic number χ(G)) for arbitrary graphs using the Hopfield neural network (HNN) model of computation. …”
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem
Published 2002“…In this paper we present a parallel algorithm to solve the above problem for arbitrary graphs using a Hopfield Neural Network model of computation. …”
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Natural optimization algorithms for the cross-dock door assignment problem
Published 2016“…The results indicate that the SS algorithm outperformed the GA, particularly for large-sized problems with a diverse reference set.…”
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A New Parallel Genetic Algorithm Model
Published 2020“…This paper presents an implementation of three Genetic Algorithm models for solving a reliability optimization problem for a redundancy system with several failure modes, a modification on a parallel a genetic algorithm model and a new parallel genetic algorithm model. …”
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A distributed genetic algorithm for deterministic and stochastic labor scheduling problems
Published 1999“…Our distributed genetic algorithm operates in parallel on a network of message-passing workstations. …”
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Using genetic algorithms to optimize software quality estimation models
Published 2004“…The main contributions of this work are two evolutionary approaches to this optimization problem. In the first approach, we assume the existence of several models, and we use a genetic algorithm to combine them, and adapt them to a given data set. …”
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
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Algorithmic Study of Online Multi-Facility Location Problems
Published 2022“…Facility location (FL) is a well-known optimization problem that asks to optimally place facilities so as to serve clients at various locations, requesting a facility service, with minimum possible costs. …”
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An evolutionary algorithm for solving the geometrically constrained site layout problem
Published 2017“…The layout problem considered in this paper is a static layout problem characterized by affinity weights used to model transportation costs between facilities and by geometric constraints between relative positions of facilities on site. …”
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A genetic-based algorithm for fuzzy unit commitment model
Published 2000“…This paper presents a fuzzy model for the unit commitment problem (UCP). …”
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Portfolio Selection Problem Using CVaR Risk Measures Equipped with DEA, PSO, and ICA Algorithms
Published 2022“…In the first method, the CVaR measurement was modeled by means of DEA, then Particle Swarm Optimization (PSO) and the Imperial Competitive Algorithm (ICA) were used to solve the proposed model. …”
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Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms
Published 2023“…Eighteen classification models were built using different classification algorithms such as Gaussian Naive Bais, Logistic Regression, k-nearest neighbors, Random Forest, and Decision Tree. …”
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A Parallel Genetic Algorithm for the Geometrically Constrained Site Layout Problem with Unequal-Size Facilities
Published 2010“…Parallel genetic algorithms techniques have been used in a variety of computer engineering and science areas. …”
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Genetic Algorithm for Solving Site Layout Problem with Unequal-Size and Constrained Facilities
Published 2002“…loosely versus tightly constrained layouts. In most problems considered where the total-objects-to-site-area ratio did not exceed 60%, the algorithm returned close to optimal solutions in a reasonable time.…”
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Estimating Construction Project Duration Using a Machine Learning Algorithm
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