Search Results - (( simulation optimization based algorithm ) OR ( based optimization modified algorithm ))
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1
A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and 2-Opt Operator
Published 2021“…The simulated Kalman filter (SKF) is an algorithm for population-based optimization based on the Kalman filter framework. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…Besides, some real data sets were examined to validate the proposed algorithm. Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
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A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and Swap Operator
Published 2021“…The simulated Kalman filter (SKF) is an algorithm for population-based optimization based on the Kalman filter framework. …”
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4
A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…This study introduces a novel meta-heuristic optimization algorithm known as quasi-oppositional modified Jaya (QOMJaya) to solve different multi-objective optimal power flow (MOOPF) problems. …”
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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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6
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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Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem
Published 2022“…Purpose – The purpose of the research is to solve Travelling Salesman Problem (TSP) using Simulated Kalman Filter (SKF) algorithm and single-solution SKF (ssSKF) algorithm based on numerical ordering technique. …”
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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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Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems
Published 2018“…Simulated Kalman Filter (SKF) is a population-based optimization algorithm which exploits the estimation capability of Kalman filter to search for a solution in a continuous search space. …”
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10
Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers
Published 2022“…Thus, seven metaheuristic algorithms: Barnacles Mating Optimizer (BMO), Marine Predators Algorithm (MPA), Moth–Flame Optimization (MFO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching–Learning-Based Optimization (TLBO) and Heap-Based Optimizer (HBO) are used to solve two objective functions: power loss and cost minimizations. …”
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Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems
Published 2018“…Simulated Kalman Filter (SKF) is a population-based optimization algorithm which exploits the estimation capability of Kalman filter to search for a solution in a continuous search space. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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13
Development of optimization Alghorithm for uncertain non-linear dynamical system
Published 2004“…Based on the results of these simulations, we compared the number of iterations needed by each algorithm to arrive at the optimal solution and the CPU time taken for each algorithm to execute the search. …”
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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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15
A modified n-th section line search in conjugate gradient methods for solving unconstrained optimization / Muhammad Imza Fakhri Jinudin
Published 2018“…These line search methods are tested based on six standard optimization test problems. …”
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16
A harmony search-based learning algorithm for epileptic seizure prediction
Published 2016“…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
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Performance Enhancement Of Artificial Bee Colony Optimization Algorithm
Published 2013“…Artificial Bee Colony (ABC) algorithm is a recently proposed bio-inspired optimization algorithm, simulating foraging phenomenon of honeybees. …”
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18
An application of teaching–learning-based optimization for solving the optimal power flow problem with stochastic wind and solar power generators
Published 2023“…This paper proposes the implementation of metaheuristic algorithm namely, teaching–learning-based optimization (TLBO) algorithm to solve optimal power flow (OPF) problem. …”
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Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm
Published 2022“…Nevertheless, many existing optimization tools for tuning the FOPID controller, which are based on multi-agent based optimization, require large number of function evaluation in their algorithm that could lead to high computational burden. …”
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