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1
Iteration strategy and ts effect towards the performance of population based metaheuristics
Published 2020“…This is an important issue to be considered when designing a new population-based metaheuristic. Three parent algorithms, namely, particle swarm optimization (PSO), gravitational search algorithm (GSA), and simulated Kalman filter (SKF) are used in this work to find a general pattern of the effect of iteration strategy towards the performance of population-based algorithms. …”
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2
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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3
Augmented model based double iterative loop techniques for integrated system optimisation and parameter estimation of large scale industrial processes
Published 1993“…The double iterative loop structures of the proposed algorithms use the real process measurement within the outer loops while the inner loops involve model based computation only. …”
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4
Finite impulse response optimizers for solving optimization problems
Published 2019“…In this work, three new estimation-based metaheuristic algorithms are introduced. The first algorithm is a single-agent-based algorithm, named Single-agent FIR optimizer (SAFIRO). …”
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5
Finite impulse response optimizers for solving optimization problems
Published 2019“…In this work, three new estimation-based metaheuristic algorithms are introduced. The first algorithm is a single-agent-based algorithm, named Single-agent FIR optimizer (SAFIRO). …”
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6
Proportional-integral control optimization using imperialist competitive algorithm
Published 2012“…ICA is one of the newest computational algorithms that emulate the process of imperialistic competition. …”
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7
Billet shape optimization for minimum forging load
Published 2008“…Finite element software (ANSYS) was used to simulate closed die forging process and then performing a series of optimization iterations in order to obtain the optimal shape of the billet based on forging load minimization. …”
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8
OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM
Published 2011“…In this thesis, a new optimization GA-based algorithm that emanates from modification of conventional GA to reduce the iterations number and the duration time, namely, semi-parallel operation genetic algorithm (SPOGA) is proposed. …”
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9
SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique
Published 2023Conference Paper -
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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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11
Tree physiology optimization on SISO and MIMO PID control tuning
Published 2018“…The iterative search of shoot towards better light supported by the root counterparts leads to an optimization idea of TPO algorithm. …”
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12
Tree physiology optimization on SISO and MIMO PID control tuning
Published 2018“…The iterative search of shoot towards better light supported by the root counterparts leads to an optimization idea of TPO algorithm. …”
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13
A conflict-based priority dispatching rule and operation-based approaches to job shops
Published 2004“…A conflict based PDR is used to schedule the job shop model by using Genetic Algorithms (GAs). …”
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Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem
Published 2022“…As a multi-agent algorithm, every agent in the population acts as a Kalman filter by using a standard Kalman filter framework, which includes a simulated measurement process and a best-so-far solution as a reference. …”
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On iterative low-complexity algorithm for optimal antenna selection and joint transmit power allocation under impact pilot contamination in downlink 5g massive MIMO systems
Published 2020“…In conclusion, the proposed low-complexity iterative algorithm can be used to maximize the EE based on the maximum transmit power , where the noise power is less than the power of the received pilot sequence.…”
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17
Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter
Published 2015“…This paper proposes three steps of improvements for identification of the nonlinear dynamic system, which exploits the concept of a state-space based time domain Volterra model. The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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Hybridizing harmony search with local search based metaheuristic for solving curriculum based university course timetabling / Juliana Wahid
Published 2017“…Harmony search algorithm (HSA) is a population-based metaheuristic optimization algorithm that imitates the music improvisation process where musicians improvise their instruments’ pitch by searching for a perfect state of harmony. …”
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19
A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites
Published 2019“…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
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20
Energy-Efficient Low-Complexity Algorithm in 5G Massive MIMO Systems
Published 2021“…This formulates the optimization problem of joint optimal antenna selection, transmits power allocation and joint user selection to mitigate inter-cellinterference in downlink multi-cell massiveMIMO systems under minimized reuse of pilot sequences based on a novel iterative low-complexity algorithm (LCA) for Newton’s methods and Lagrange multipliers. …”
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