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1
Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems
Published 2021“…In addition, 2 types of scout bee were used for to intensify the probability property of the algorithm. …”
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Performance Enhancement Of Artificial Bee Colony Optimization Algorithm
Published 2013“…Artificial Bee Colony (ABC) algorithm is a recently proposed bio-inspired optimization algorithm, simulating foraging phenomenon of honeybees. …”
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3
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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Battery management optimization and lifecycle impact analysis for microgrid operation with V2G implementation / Muhammad Sufyan
Published 2019“…The proposed energy management approach is solved using firefly algorithm, artificial bee colony, harmony search algorithm and particle swarm optimization. …”
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5
Hybridization Of Deterministic And Metaheuristic Approaches In Global Optimization
Published 2019“…In the analysis of the literature, Artificial Bees Colony (ABC) Algorithm has been selected as the metaheuristic approach to be improved its capability and efficiency to solve the global optimization problems. …”
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6
Enhanced ABD-LSSVM for energy fuel price prediction
Published 2013“…This paper presents an enhanced Artificial Bee Colony (eABC)based on Lévy Probability Distribution (LPD) and conventional mutation. …”
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Enhanced ABC-LSSVM For Energy Fuel Price Prediction
Published 2014“…This paper presents an enhanced Artifi cial Bee Colony (eABC) based on Lévy Probability Distribution (LPD) and conventional mutation. …”
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Determining penetration limit of central distributed generation topology in radial distribution networks
Published 2021“…The biogeography based optimization method has been proven to have better performance than artificial bee colony, genetic algorithm, particle swarm optimization, hybrid of particle swarm optimization and constriction factor approach, and hybrid of ant colony optimization and artificial bee colony methods in terms of active power loss reduction. …”
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9
Sizing of a standalone photovoltaic water pumping system using a multi-objective evolutionary algorithm
Published 2023“…Algorithms; Costs; Evolutionary algorithms; Life cycle; Multiobjective optimization; Optimization; Probability; Pumping plants; Pumps; Water levels; Differential Evolution; Economic objectives; Multi objective evolutionary algorithms; Non-dominated Sorting; Objective functions; Photovoltaic; Photovoltaic water pumping; Pumping systems; Loss of load probability; algorithm; cost analysis; drawdown; multicriteria analysis; optimization; performance assessment; photovoltaic system; probability; pumping; water demand…”
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Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
Published 2023“…Meta-heuristic algorithms have become popular in finding optimal solutions for nonlinear complex problems. …”
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Q-learning whale optimization algorithm for test suite generation with constraints support
Published 2023“…This paper introduces a new variant of a metaheuristic algorithm based on the whale optimization algorithm (WOA), the Q-learning algorithm and the Exponential Monte Carlo Acceptance Probability called (QWOA-EMC). …”
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A proposed genetic algorithm to optimize service restoration in electrical networks with respect to the probability of transformers failure
Published 2010“…In many researches a Genetic Algorithm is employed as a powerful tool to solve this multi-objective, multi-constraint optimization problem. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…They are Cross Entropy and also Genetic Algorithm. CE is a new algorithm that was recently developed using probability. …”
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14
Techno-economical optimization of hybrid pv/wind/battery system using Neuro-Fuzzy
Published 2023Subjects:Article -
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Power allocation optimization for oam-mimo systems with unaligned antennas
Published 2022“…Numerical results show that the error probability reduction of the OAM-MIMO transmission system by using the proposed optimization algorithm is up to 26.1 dB.…”
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Multiobjective differential evolution algorithm-based sizing of a standalone photovoltaic water pumping system
Published 2023“…Algorithms; Costs; Evolutionary algorithms; Flow of water; Life cycle; Meteorology; Multiobjective optimization; Optimization; Probability; Pumping plants; Pumps; Solar power generation; Differential Evolution; Lifecycle costs; Meteorological data; Multi-objective differential evolution algorithms; Objective functions; Photovoltaic; Photovoltaic water pumping; Solar waters; Loss of load probability…”
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The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment
Published 2016“…Therefore, the IE algorithm exhibits significant potential for UAV path planning optimization…”
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18
An empirical study of density and distribution functions for ant swarm optimized rough reducts
Published 2011“…Ant Swarm Optimization refers to the hybridization of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms to enhance optimization performance. …”
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Book Chapter -
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Optimization of job scheduling in a machine shop using genetic algorithm
Published 2002“…A modified version of GA known as string GA has been used to get the near optimal cycle time for permutation analysis. An experiment has been carried out with 2 iv 5 resolution to find the significance of five parameters of GA, namely population size, maximum generation, probability of crossing, probability of mutation and crossover operators. …”
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Optimization of job scheduling in a machine shop using genetic algorithm
Published 2002“…A modified version of GA known as string GA has been used to get the near optimal cycle time for permutation analysis. An experiment has been carried out with 2 iv 5 resolution to find the significance of five parameters of GA, namely population size, maximum generation, probability of crossing, probability of mutation and crossover operators. …”
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