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1
Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…The newly proposed algorithm was tested using a set of standard benchmark functions with different searching space and global optima placement. …”
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2
Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem
Published 2023“…This work introduced a new Binary Whale Optimization Algorithm, which utilized a novel time-varying modified Sigmoid transfer function with a modified logarithmic decreasing time-varying update strategy to improve the balancing of exploration and exploitation in WOA. …”
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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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4
A modified discrete filled function algorithm for solving nonlinear discrete optimization problems
Published 2012“…The discrete filled function method is a global optimization tool for searching for best solution amongst multiple local optima.This method has proven useful for solving large-scale discrete optimization problems.In this paper, we consider a standard discrete filled function algorithm in the literature and then propose a modification to increase its efficiency.…”
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5
Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning
Published 2019“…Many variants have been developed to cope with this problem and improve algorithm performance. In this paper, a hybrid algorithm of HS with grey wolf optimizer (GWO) has been developed to solve the problem of HS parameter selection. …”
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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
Optimal power flow using the Jaya algorithm
Published 2016“…This paper presents application of a new effective metaheuristic optimization method namely, the Jaya algorithm to deal with different optimum power flow (OPF) problems. …”
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Modification of the ant colony optimization algorithm for solving multi-agent task allocation problem in agricultural application
Published 2024“…By employing such a function, simulation results show that the total resource used by the agents and total communication cost can be optimized. …”
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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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10
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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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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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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13
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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14
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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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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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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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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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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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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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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