Search Results - (( using adaptive problem algorithm ) OR ( simulation optimization based algorithm ))
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1
Opposition-based learning simulated kalman filter for Numerical optimization problems
Published 2016“…Simulated Kalman Filter (SKF) optimization algorithm is a population-based optimizer operated mainly based on Kalman filtering. …”
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Research Book Profile -
2
Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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3
Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Published 2023“…The evolutionary algorithm has been extensively used to solve a range of combinatorial optimization problems. …”
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4
New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…The increasing interest among researchers in the application of metaheuristic algorithms for search optimization has resulted in notable progress, especially in tackling single objective optimization problems. …”
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5
Adaptive DNA computing algorithm by using PCR and restriction enzyme
Published 2004“…Finally, we go on to propose applying adaptive algorithm to the chemistry experiment which used the actual DNA molecules for soiving B universal problem.…”
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6
Fuzzy adaptive emperor penguin optimizer for global optimization problems
Published 2023“…The Emperor Penguin Optimizer (EPO) is a recently developed population-based metaheuristic algorithm that simulates the huddling behaviour of emperor penguins. …”
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7
Exponentially adaptive sine-cosine algorithm for global optimization
Published 2019“…It is widely used to solve various optimization problems. However the algorithm performance in terms of accuracy is not at optimum level. …”
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8
An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem
Published 2022“…Emperor Penguin Optimizer (EPO) is a recently developed population-based meta-heuristic algorithm that simulates the huddling behavior of emperor penguins. …”
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9
Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization
Published 2018“…Many meta-heuristic algorithms have been developed to date (e.g. Simulated Annealing (SA), Particle Swarm Optimization (PSO), Teaching Learning based Optimization (TLBO), Grey Wolf Optimizer(GWO) to name a few). …”
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10
Enhanced utility accrual scheduling algorithms for adaptive real time system.
Published 2009“…We compared the performances of these algorithms by using discrete event simulation. Results: The proposed PUAS algorithm achieved the highest accrued utility for the entire load range. …”
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11
Estimation-based Metaheuristics: A New Branch of Computational Intelligence
Published 2016“…The experimental results show that the estimation-based metaheuristic is a promising approach to solving global optimization problem and demonstrates a competitive performance to some well-known metaheuristic algorithms…”
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12
Fpga Implementation Of Metaheuristic Optimization Algorithm
Published 2022“…Metaheuristic algorithms are gaining popularity amongst researchers due to their ability to solve nonlinear optimization problems as well as the ability to be adapted to solve a variety of problems. …”
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Undergraduates Project Papers -
13
FPGA implementation of metaheuristic optimization algorithm
Published 2023“…Metaheuristic algorithms are gaining popularity amongst researchers due to their ability to solve nonlinear optimization problems as well as the ability to be adapted to solve a variety of problems. …”
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14
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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15
Methane plume localization with enhanced self-best reduction and Gaussian improved particle swarm optimization (GiPSO)
Published 2024“…Adapting the Gaussian gas plume model in the simulation provides the experiment with a realistic optimization problem for GiPSO to optimize in the simulation, where we can test the engagement of dynamically challenging optimization problems such as gas plume dispersions. …”
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16
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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17
Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems
Published 2024“…The main motivations for investigating IWD algorithm are: (i) IWD has been successfully employed to solve many optimization problems. …”
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18
Adaptive Line Enhancer with Selectable Algorithms based on Noise Eigenvalue Spread
Published 2016“…The simulation results showed the capability of proposed algorithm to eliminate different types of environmental noise with fast convergence, reduction in computational complexity and improvement in signal-to-noise ratio when compared with an equivalent system using a single adaptive algorithm. …”
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19
An adaptively switching iteration strategy for population based metaheuristics / Nor Azlina Ab. Aziz
Published 2017“…Experiments conducted using three parent algorithms namely particle swarm optimization (PSO), which is a popular population-based optimizer with population and individual memories, gravitational search algorithm (GSA), a memoryless young optimizer, and simulated Kalman filter (SKF), a newly introduced optimization algorithm that use population’s memory to guide an agent’s search, show that iteration strategy is an algorithm dependent parameter as well as function dependent. …”
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20
Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio...
Published 2023“…Comparing this developed algorithm with other algorithms shows its superiority in multi-objective optimization (MOO) evaluation metrics. …”
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