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1
Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning
Published 2019“…Then, a modified version of opposition-based learning technique has been applied on the hybrid algorithm to improve the HS exploration because HS easily gets trapped into local optima. …”
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2
Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane
Published 2021“…In the HMVOSCA algorithm, the new position updating mechanism of the traditional MVO method is modified based on the sine function and cosine function which is taken from the Sine Cosine Algorithm (SCA). …”
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3
An experimental study of modified black hole algorithms
Published 2018“…The black hole has been found theoretically in the studies of the universe as a star having massive mass and gravity. The BH algorithm is a population-based method which uses more than one agent to find a solution in a search space. …”
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4
New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…However, the complexity significantly rises when dealing with multi objective functions. The Modified Adaptive Bats Sonar Algorithm (MABSA), initially designed for single objective optimization and inspired by colony bats' echolocation, has demonstrated efficiency with its simple structure and reduced computation time. …”
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5
Optimal power flow using the Jaya algorithm
Published 2016“…Unlike other population-based optimization methods, no algorithm-particular controlling parameters are required for this algorithm. …”
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6
A modified flower pollination algorithm and carnivorous plant algorithm for solving engineering optimization problem
Published 2021“…Flower pollination algorithm (FPA) is a biomimicry optimisation algorithm inspired by natural pollination. …”
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7
Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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8
Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem
Published 2022“…Research limitations – The experiment of this research only uses 15 types of TSP function which are TSP functions that are evaluated using Euclidean distance. …”
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9
An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion
Published 2018“…We have chosen four neighborhood based algorithms which are commonly used in optimization problems and divided them in newly implemented and re-implemented category. …”
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10
A Modified Gravitational Search Algorithm for Discrete Optimization Problem
Published 2014“…This paper presents a modified Gravitational Search Algorithm (GSA) called Discrete Gravitational Search Algorithm (DGSA) for discrete optimization problems. …”
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11
Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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12
An Improved Artificial Immune System Based On Antibody Reminder Method For Mathematical Function Optimization
Published 2010“…However, the CSA convergence and accuracy can be improved further because the hyper mutation in CSA itself cannot always guarantee a better solution. Alternatively, Genetic Algorithms (GAS) and Particle Swarm Optimization (PSO) have been used efficiently in solving complex optimization problems, but they have a tendency to converge prematurely. …”
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13
Artificial Immune System Based Remainder Method for Multimodal Mathematical Function Optimization
Published 2011“…Simulation results show that the proposed algorithm is able to enhance the performance of the conventional CSA in terms of accuracy and stability for single objective functions.…”
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14
OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM
Published 2011“…The aim of the algorithm is to improve a controller performance (minimize the overshoot, settling time, IAE/ITAE and achieving zero steady state error) when used for a DC servomotor application. …”
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15
Modified Opposition Based Learning to Improve Harmony Search Variants Exploration
Published 2020“…Harmony Search Algorithm (HS) is a well-known optimization algorithm with strong and robust exploitation process. …”
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16
An improved artificial immune system based on antibody remainder method for mathematical function optimization
Published 2023“…However, the CSA convergence and accuracy can be improved further because the hypermutation in CSA itself cannot always guarantee a better solution. Alternatively, Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) have been used efficiently in solving complex optimization problems, but they have a tendency to converge prematurely. …”
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17
Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…The flexibility of a genetic algorithm allows various strategies to be applied to it. …”
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18
Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain
Published 2020“…The objectives of the studies are to develop a new optimization technique termed as Modified Firefly Algorithm (MFA) for minimizing the relay operating time, to develop a Multi-Objective Modified Firefly Algorithm (MOMFA) for minimizing both the total relay operating time and relay coordination time and to develop an integrated optimal predictor termed as Modified Firefly Algorithm-Artificial Neural Network (MFA-ANN) for accurate prediction of relay operating time. …”
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19
Hybrid evolutionary optimization algorithms: A case study in manufacturing industry
Published 2014“…Such complex problems of vagueness and uncertainty can be handled by the hybrid evolutionary intelligence algorithms. In this chapter, a new hybrid evolutionary optimization based methodology using a specific non-linear membership function, named as modified S-curve membership function, is proposed. …”
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20
Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…This paper proposes a new SGD algorithm with modified stepsize that employs function scaling strategy. …”
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