Search Results - (( simulation optimization bees algorithm ) OR ( swarm optimization method algorithm ))
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Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…This research proposed an improved CS called hybrid Accelerated Cuckoo Particle Swarm Optimization algorithm (HACPSO) with Accelerated particle Swarm Optimization (APSO) algorithm. …”
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System performances analysis of reservoir optimization–simulation model in application of artificial bee colony algorithm
Published 2018“…Particle swarm optimization, genetic algorithm and neural network-based stochastic dynamic programming are also used in a view of comparing model performances. …”
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A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer
Published 2019“…In this research, a novel swarm-based metaheuristic algorithm which depends on the behavior of nomadic people was developed, it is called ‘‘Nomadic People Optimizer (NPO)’’. …”
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Solving large-scale problems using multi-swarm particle swarm approach
Published 2018“…The results showed that the proposed PSO algorithm outperformed the other algorithms in terms of the optimal solutions and the convergence.…”
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A Chameleon algorithm for solving economic dispatch problem in microgrid system
Published 2024“…The obtained results from the simulation are compared with the conventional metaheuristic algorithms which have been used in previous studies, such as particle swarm optimization (PSO), genetic algorithm (GA), and artificial bee colony (ABC). …”
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Optimization of fed-batch fermentation processes using the Backtracking Search Algorithm
Published 2018“…DE traditionally performs better than other evolutionary algorithms and swarm intelligence techniques in optimization of fed-batch fermentation. …”
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Optimization of economic lot scheduling problem with backordering and shelf-life considerations using calibrated metaheuristic algorithms
Published 2015“…Efficient search procedures are presented to obtain the optimum solutions by employing four well-known metaheuristic algorithms, namely genetic algorithm (GA), particle swarm optimization (PSO), simulated annealing (SA), and artificial bee colony (ABC). …”
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A hybrid of Simple Constrained artificial bee colony algorithm and flux balance analysis for enhancing Lactate and Succinate in Escherichia Coli
Published 2018“…The hybrid algorithm employed the Simple Constrained Artificial Bee Colony (SCABC) algorithm, using swarm intelligence as an optimization algorithm to optimize the objective function, where lactate and succinate productions are maximized by simulating gene knockout in E. coli. …”
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Application of intelligent optimization techniques and investigating the effect of reservoir size in calibrating the reservoir operating policy
Published 2023“…Particle swarm optimization, genetic algorithm and neural network-based stochastic dynamic programming are used to compare the model performances. …”
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Structural optimization of 4-DOF agricultural robot arm
Published 2024“…The comparison between artificial bee colony (ABC) and particle swarm optimization (PSO) is studied. …”
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Artificial bee colony for inventory routing problem with backordering
Published 2014“…The objective of IRPBis to minimize the overall cost such that transportation cost, inventory cost and backorder cost is optimal. We propose a metaheuristic method, Artificial Bee Colony (ABC) to solve the IRPB.The ABCalgorithm is a swarm based heuristics which simulates the intelligent foraging behaviour of a honey bee swarm and sharing that information of the food sources with the bees in the nest. …”
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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter
Published 2015“…The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter
Published 2015“…The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…There is no particular study which focuses on the optimization and prediction of blades parameters using natural inspired algorithms namely Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and Adaptive Neuro-fuzzy Interface System (ANFIS) respectively for optimal power coefficient (�436�45D ). …”
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A Comparative Study of Optimization Methods for 33kV Distribution Network Feeder Reconfiguration
Published 2014“…In this paper, a comparative study has been made by using several optimization methods which are Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). …”
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A comparative study of optimization methods for 33kV distribution network feeder reconfiguration
Published 2014“…In this paper, a comparative study has been made by using several optimization methods which are Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). …”
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Metaheuristic algorithms for solving lot-sizing and scheduling problems in single and multi-plant environments / Maryam Mohammadi
Published 2015“…Metaheuristic approaches namely genetic algorithm, particle swarm optimization, artificial bee colony, simulated annealing, and imperialist competitive algorithm are adopted for the optimization procedures. …”
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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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