Search Results - (( global optimization method algorithm ) OR ( probable distribution method algorithm ))
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Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem
Published 2008“…Genetic Algorithm as population-based methods are better identifying promising areas in the search space, while Tabu Search and Simulated Annealing as trajectory methods are better in exploring promising areas in search space. …”
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Monograph -
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A new hybrid GA−ACO−PSO algorithm for solving various engineering design problems
Published 2019“…The intention of this hybridization is to further enhance the exploratory and exploitative search capabilities involving simple concepts. The proposed algorithm adopts the combined discrete and continuous probability distribution scheme of ant colony optimization (ACO) to specifically assist genetic algorithm in the aspect of exploratory search. …”
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Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching
Published 2016“…For parameter estimation, the simulated annealing global optimization routine and an EM-algorithm type approach for maximum likelihood estimation are studied. …”
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Optimal performance of stand-alone hybrid microgrid systems based on integrated techno-economic-environmental energy management strategy using the grey wolf optimizer
Published 2024“…Grey Wolf Optimizer (GWO) was utilized to find the optimal size of the hybrid Microgrid components and calculate the multi-objective function with and without the proposed management method. …”
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Multi-objective portfolio selection with skewness preference: An application to the stock and electricity markets / Karoon Suksonghong
Published 2014“…The superiority of this method is its ability to generate a set of MVS efficient portfolios within a single run of algorithm. …”
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A Hybrid Method Based on Cuckoo Search Algorithm for Global Optimization Problems
Published 2018“…However, it undergoes the premature convergence problem for high dimensional problems because the algorithm converges rapidly. Therefore, we proposed a robust approach to solve this issue by hybridizing optimization algorithm, which is a combination of Cuckoo search algorithm and Hill climbing called CSAHC discovers many local optimum traps by using local and global searches, although the local search method is trapped at the local minimum point. …”
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Global gbest guided-artificial bee colony algorithm for numerical function optimization
Published 2018“…The two well-known honeybees-based upgraded algorithms, Gbest Guided Artificial Bee Colony (GGABC) and Global Artificial Bee Colony Search (GABCS), use the foraging behavior of the global best and guided best honeybees for solving complex optimization tasks. …”
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A Comparison of Particle Swarm optimization and Global African Buffalo Optimization
Published 2020“…However, in this paper, a comparison between Particle Swarm Optimization (PSO) and Global African Buffalo Optimization (GABO) algorithms was performed. …”
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Conference or Workshop Item -
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Hybridizing Invasive Weed Optimization with Firefly Algorithm for Unconstrained and Constrained Optimization Problems
Published 2017“…This study presents a hybrid invasive weed firefly optimization (HIWFO) algorithm for global optimization problems. …”
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Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis
Published 2014“…The Particle Swarm Optimization (PSO) Algorithm is a popular optimization method that is widely used in various applications, due to its simplicity and capability in obtaining optimal results. …”
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A Novel Discrete Filled Function Algorithm in Solving Discrete Optimization Problems (S/O: 12408)
Published 2016“…Several global methods have been proposed for solving discrete optimization problems. …”
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Monograph -
12
Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost
Published 2024“…In this method, the Gray Wolf optimized algorithm (EBGWO) is further optimized by particle swarm optimization (PSO), and when combined with it, the convergence performance of the model is improved, the parameters of the model are reduced, and the model is simplified. …”
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Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications
Published 2023“…Carbon; Decarbonization; Electric energy storage; Fossil fuels; Global warming; Renewable energy resources; Carbon emissions; Decarbonisation; Energy storage system; Method; Microgrid; Optimal energy; Optimization algorithms; Sizing; Storage systems; System sizings; Cost effectiveness…”
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Global optimization method for continuous - Time sensor scheduling
Published 2010“…We consider a situation in which several sensors are used to collect data for signal processing since operating multiple sensors simultaneously canses system interference, only one sensor can be active at any one time.The problem of scheduling a discrete-valued optimal control problem.This problem cannot be solved using conventional optimization problem.The Transformed problem is then decomposed into a bi-level optimization problem, which is solved using a discreate filled function method in conjunction with a conventional optimal control algorithm.Numerical results show that our algorithm is robust, efficient, and reliable in attaining a near globally optimal solution.…”
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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023Conference Paper -
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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…One of the more recent global optimization tools in the area of discrete optimization is known as the discrete filled function method. …”
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Thesis -
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Hybridization Of Deterministic And Metaheuristic Approaches In Global Optimization
Published 2019“…In another hand, numerical results of ABCED Conjugate Gradient Methods also achieved up to 80.95% of the selected benchmark global optimization been solved successfully. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Thus, proposing the method of reestimating the dropping functions in the RED algorithm. …”
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