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1
A genetic-based algorithm for fuzzy unit commitment model
Published 2000“…The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. …”
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An algorithm for solving bond pricing problem
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An Uncertainty Based Genetic Algorithm Approach for Project Resource Scheduling
Published 2016“…The work presented in thesis add to the existing literature in a proposing the use of a genetic algorithm uncertain approach to resource- scheduling in projects. …”
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Genetic Algorithm Analysis using the Graph Coloring Method for Solving the University Timetable Problem
Published 2018“…Genetic algorithms were successfully useful to solve many optimization problems including the university Timetable Problem. …”
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Parameter Estimation Of Wiener-Hammerstein Models Via Genetic Algorithms
Published 2020“…In this paper, a modified genetic algorithm is used as a procedure to solve the parameter identification problem of the nonlinear Wiener-Hammerstein models. …”
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An evolutionary algorithm for solving the geometrically constrained site layout problem
Published 2017“…This paper presents an investigation of applying an evolutionary approach to optimally solve the aforementioned layout problem. The proposed algorithm is two-phases: an initialization phase that generates an initial population of layouts through a sequence of mutation operations, and a reproduction phase that evolve the layouts generated in phase one through a sequence of genetic operations aiming at finding an optimal layout. …”
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7
Efficient convex-elastic net algorithm to solve the Euclideantraveling salesman problem
Published 1998“…This paper describes a hybrid algorithm that combines an adaptive-type neural network algorithm and a nondeterministic iterative algorithm to solve the Euclidean traveling salesman problem (E-TSP). …”
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Modified clarke wright algorithms for solving the realistic vehicle routing problem
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High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm
Published 2025“…The trigonometric function-based sine cosine algorithm (SCA) may solve such problems, but it traps in local optima, making it inappropriate for larger optimization tasks. …”
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Fuzzy genetic algorithm for floorplanning
Published 2020“…Genetic algorithms (GAs) have been found to be very effective in solving numerous optimization problems, especially those with many (possibly) conflicting and noisy objectives. …”
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11
Automating UML Models Refactoring using Search-Based Algorithms
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12
Genetic Algorithm for Solving Site Layout Problem with Unequal-Size and Constrained Facilities
Published 2002“…This paper presents an investigation of the applicability of a genetic approach for solving the construction site layout problem. This problem involves coordinating the use of limited site space to accommodate temporary facilities so that transportation cost of materials is minimized. …”
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Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm
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Decomposition method for solving a nonlinear business cycle model
Published 2003“…A numerical algorithm based on a decomposition scheme is implemented for the approximate solution of the model. …”
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Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology
Published 2023“…In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. …”
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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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Modeling and Control of a Robot Based Rehabilitation System for the Head-Neck Joint
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A neural networks algorithm for data path synthesis
Published 2003“…The algorithm is driven by a motion equation that determines the neurons firing conditions based on the modified Hopfield neural network model of computation. …”
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A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008)
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