Search Results - (( solution location based algorithm ) OR ( variable optimization method algorithm ))
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Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly
Published 2023“…The first method is greedy heuristic method. Greedy heuristics is a type of optimization algorithm that makes decisions based on locally optimal solutions. …”
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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…Furthermore, variable switching times are known to cause problems in the implementation of any numerical algorithm due to the variable location of discontinuities in the dynamics. …”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems
Published 2016“…Throughout the years, there has been a shift in focus on constructing new crossover and mutation operators to improve the performance of GA in function optimization. GA operators employ two main strategies; that is, exploration and exploitation to locate the optimum solutions. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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Hospital site suitability assessment using three machine learning approaches: evidence from the Gaza strip in Palestine
Published 2021“…The study aims to find an optimal solution for a suitable hospital location through suitability mapping using relevant environmental, topographic, and geodemographic parameters and their variable criteria. …”
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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
Published 2014“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization
Published 2017“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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Optimization Of Bar Linkage By Using Genetic Algorithms
Published 2005“…This thesis presents the method of using simple Genetic Algorithms (GAs) in optimizing the size of bar linkage with discrete design variables and continues design variables. …”
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Mine blast algorithm for optimization of truss structures with discrete variables
Published 2012“…In this study a novel optimization method is presented, the so called mine blast algorithm (MBA). …”
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Enhanced cell-based algorithm with dynamic radius in solving capacitated multi-source weber problem
Published 2021“…Random selection of facility location in a Cell-based approach may cause infeasible or worse solutions. …”
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A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
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A MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR WELLBORE TRAJECTORY DESIGN
Published 2021“…To address this issue, a new hybridization of cellular automata (CA) technique with grey wolf optimization (GWO) and particle swarm optimization (PSO) algorithms is proposed in this work which solves these three optimization objectives of drilling through 17 tuning variables. …”
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Modification of particle swarm optimization algorithm for optimization of discrete values
Published 2011“…Among the stochastic optimization methods is Particle Swarm Optimization (PSO). …”
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Research Reports -
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Harmony search algorithm for curriculum-based course timetabling problem
Published 2013“…With proper modification in terms of the approach in this algorithm would make the algorithm perform better on curriculum-based course timetabling.…”
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Harmony search algorithm for curriculum-based course timetabling problem
Published 2013“…However, the algorithm produced results that were not comparatively better than those previously known as best solution.With proper modification in terms of the approach in this algorithm would make the algorithm perform better on curriculum-based course timetabling.…”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025“…After the variable selection process using the proposed method, the optimal prediction model is now formulated with a lesser variable, making it less complex and computationally fast. ? …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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