Search Results - (( using optimization problem algorithm ) OR ( using function means algorithm ))
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Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…Stochastic gradient descent (SGD) is one of the most common algorithms used in solving large unconstrained optimization problems. …”
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2
Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…We introduced two new approaches to normalization techniques to enhance the K-Means algorithms. This is to remedy the problem of using the existing Min-Max (MM) and Decimal Scaling (DS) techniques, which have overflow weakness. …”
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3
Levy tunicate swarm algorithm for solving numerical and real-world optimization problems
Published 2022“…The proposed Levy Tunicate Swarm Algorithm (LTSA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic algorithm called Tunicate Swarm Algorithm (TSA) to solve numerical and real-world optimization problems. …”
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4
Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…Instead of solving the original optimal control problem, the model-based optimal control problem is solved. …”
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5
Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
Published 2023“…The statistical tools (Absolute Mean Error & Fried Man) are used to rank the performance of all algorithms. …”
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The effect of job satisfaction on the relationship between organizational culture and organizational performance
Published 2023“…The statistical tools (Absolute Mean Error & Fried Man) are used to rank the performance of all algorithms. …”
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8
Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems
Published 2021“…This study seeks to solve this problem using Artificial Bee Colony (ABC) Algorithm along with the proposed Discrete Nearest Neighborhood Algorithm (DNNA). …”
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9
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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10
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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11
Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems
Published 2014“…Genetic algorithm has recorded of huge success in solving NP-Complete optimization problems with similar nature to this problem. …”
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12
The fusion of particle swarm optimization (PSO) and interior point method (IPM) as cooperative movement control algorithm in Swarm Robotics / Dada Emmanuel Gbenga
Published 2016“…We also compared the performance of pdAPSO and pdPSO with 9 state of the art PSO algorithms using 12 benchmark functions. Our proposed algorithms have mean dependability of 80.4% for pdAPSO and 69.69% for pdPSO. …”
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13
Crossover and mutation operators of real coded genetic algorithms for global optimization problems
Published 2016“…The rationale behind developing algorithms using real encoding of chromosome representations is the limitations of binary encoding. …”
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14
A MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR WELLBORE TRAJECTORY DESIGN
Published 2021“…Wellbore trajectory design is a nonlinear and constrained mathematical optimization problem used to build a cost-efficient, safe, and easily reachable trajectory. …”
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15
Optimization of multi-holes drilling toolpath using tiki-taka algorithm
Published 2024“…A computational experiment was conducted on 12 test problems across small, medium, and large problem categories using the TTA, then compared with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Crayfish Optimization Algorithm (COA), and Geometric Mean Optimizer (GMO). …”
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16
Comparative analysis of line search methods in the Steepest Descent algorithm for unconstrained optimization problems / Ahmad Zikri Shukeri, Puteri Qurratu Ain Megat Sulzamzamendi...
Published 2024“…The result from this study is choosing FMRI algorithm using exact line search to get faster convergence rate which means that the algorithm achieves a high level of accuracy in fewer iterations compared to using other algorithms and inexact line search.…”
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Student Project -
17
Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The new proposed method (MBPSO+MKN+GK) Gustafson- Kessel algorithm (GK)integrated with modified of Kohonen Network algorithm (MKN)and modified binary particle swarm optimization (MBPSO) was used to classify the credit scoring data. …”
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Seed disperser ant algorithm for optimization / Chang Wen Liang
Published 2018“…The classical benchmark problems and composite benchmark functions from Congress on Evolutionary Computation (CEC) 2005 special session is used for validate SDAA. …”
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19
Self-adaptive conjugate method for a robust and efficient performance measure approach for reliability-based design optimization
Published 2018“…The advanced mean value and hybrid mean value methods are commonly used to evaluate the probabilistic constraint of reliability-based design optimization (RBDO) problems. …”
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Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals
Published 2012“…Therefore, two meta-heuristic algorithms, namely genetic algorithm (GA) and simulated annealing (SA) algorithm, were developed to optimize the integrated scheduling of handling equipment. …”
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