Search Results - (( developing general function algorithm ) OR ( a simulation optimization algorithm ))
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1
A discrete simulated kalman filter optimizer for combinatorial optimization problems
Published 2022“…An example of a numerical algorithm is the simulated Kalman filter (SKF). …”
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2
New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…In the fourth phase, the newly developed algorithm undergoes testing on the formulated ROOPs and compared to several contemporary optimizer algorithms. …”
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3
A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…This research focuses on developing a novel path planning algorithm, called Generalized Laser Simulator (GLS), to solve the path planning problem of mobile robots in a constrained environment. …”
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Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions
Published 2014“…Over the last 30 years, many meta-heuristic algorithms have been developed in the literature including that of Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search Algorithm (HS) to name a few. …”
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6
Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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A discrete event simulation framework for utility accrual scheduling algorithm in uniprocessor environment
Published 2011“…Approach: The study focused on the proposed and the development of an event based discrete event simulator for the existing General Utility Scheduling (GUS) to facilitate the reuse of the algorithm under a common simulation environment. …”
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
Published 2011“…Particularly, GA is utilized to determine the optimal number of hidden layers, number of neurons in each hidden layer, type of training algorithm, type of activation function of hidden and output neurons, initial weight, learning rate, momentum term, and epoch size of a multilayer feed-forward ANN. …”
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9
The compact genetic algorithm for likelihood estimator of first order moving average model
Published 2012“…Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. …”
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10
Modelling and optimization of a transit services with feeder bus and rail system / Mohammadhadi Almasi
Published 2015“…This is followed by application of the improved model to the benchmark and Petaling Jaya study areas. In this study, optimized transit services and coordinated schedules are developed using metaheuristic algorithms such as genetic algorithm (GA), particle swarm optimization (PSO), water cycle algorithm (WCA) and imperialist competitive algorithm (ICA). …”
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11
Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2013“…This paper details an improved modeling technique for a photovoltaic (PV) module; utilizing the optimization ability of a genetic algorithm, with different parameters of the PV module being computed via this approach. …”
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HSO: A hybrid swarm optimization algorithm for reducing energy consumption in the cloudlets
Published 2018“…There was also a decrease in the node loss which allowed the optimization algorithm to achieve a minimal overhead on cloud compute resources while still saving energy significantly. …”
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OPTIMIZING HYBRID ELECTRIC VEHICLE ENERGY UTILIZATION BASED ON PARTICLE SWARM OPTIMIZATION ALGORITHM
Published 2023“…There are challenges in designing a vehicle, albeit improving a conventional vehicle to a hybrid electric vehicle (HEV) and achieving the optimal power balance between power sources which are the internal combustion engine (ICE) and the electric motor (EM). …”
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Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems
Published 2024“…The empirical assessment of these proposed methods encompasses a diverse set of 23 benchmark functions, demonstrating their efficacy comparable to well-established metaheuristic algorithms such as as the Grey Wolf Optimizer (GWO), Multi-Verse Optimization (MVO), Sine Cosine Algorithm (SCA), Ant Lion Optimizer (ALO), Moth-Flame Optimization Algorithm (MFO), and Grasshopper Optimization Algorithm (GOA). …”
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15
A discrete event simulation for utility accrual scheduling in uniprocessor environment
Published 2011“…This research has focused on the proposed and the development of an event based discrete event simulator for the existing General Utility Scheduling (GUS) to facilitate the reuse of the algorithm under a common simulation environment. …”
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16
Fuzzy adaptive emperor penguin optimizer for global optimization problems
Published 2023“…The Emperor Penguin Optimizer (EPO) is a recently developed population-based metaheuristic algorithm that simulates the huddling behaviour of emperor penguins. …”
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17
Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network
Published 2022“…As for multi-objective functions associated with the optimisation problem, a weight-sum method is typically used to determine each objective function's coefficient factors (CF). …”
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18
Modelling Autonomous Evacuation Navigation System (AENS) for optimal route using Dijkstra's algorithm
Published 2016“…Additionally, the hypothesis result shows a significant difference in evacuation time taken using AENS for simulation and experiment result respectively. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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Iteration strategy and ts effect towards the performance of population based metaheuristics
Published 2020“…Metaheuristics algorithms solve optimization problems by repeating a set of procedures. …”
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