Search Results - (( simulation simulation approach algorithm ) OR ( using optimization problem algorithm ))
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1
Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm
Published 2016“…To evaluate the performance of the Simulated Kalman Filter algorithm, it is applied to 30 benchmark functions of CEC 2014 for real-parameter single objective optimization problems. …”
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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
Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
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4
Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem
Published 2022“…Most metaheuristic algorithms are designed for continuous optimization problem. …”
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5
Angle Modulated Simulated Kalman Filter Algorithm for Combinatorial Optimization Problems
Published 2016“…However, the SKF is only capable to solve continuous numerical optimization problem. In order to solve discrete optimization problems, the SKF algorithm is combined with an angle modulated approach. …”
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6
Optimization of turning parameters using genetic algorithm method
Published 2008“…The MATLAB software will be use to develop the GA simulation. An example to apply the Genetic Algorithm to the problem has been presented at the end of this paper to give more understanding picture from the application of the system and how its work. …”
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7
A Kalman Filter Approach for Solving Unimodal Optimization Problems
Published 2015“…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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8
A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…Ant colony optimization (ACO) is a metaheuristic approach inspired from the behaviour of natural ants and can be used to solve a variety of combinatorial optimization problems. …”
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9
Development of optimization Alghorithm for uncertain non-linear dynamical system
Published 2004“…This study succeeded in overcoming the problem of slow convergence and with the modifications, the new algorithms become more efficient in solving the optimal control problems.…”
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10
African Buffalo Optimization (ABO): A New Metaheuristic Algorithm
Published 2015“…When compared to the Ant Colony Optimization algorithm, Simulated Annealing and Genetic Algorithm, the results obtained from African Buffalo Optimization show that the algorithm works well and can be extended to solving problems like: path planning, scheduling, vehicle routing in addition to other constraint-driven problems.…”
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11
A branch and bound and simulated annealing approach for job shop scheduling
Published 2004“…In the branch and bound approach, the job shop scheduling problem is represented by a disjunctive graph, then the optimal schedule is obtained using the branch and bound algorithm while simulated annealing is a local search based algorithm which will slightly perturb the initial feasible solution to decrease the makespan. …”
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12
An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach
Published 2017“…This study associates an intelligent voltage controller based PI approach for PV electrical inverter by employing a meta-heuristic optimization algorithmic called a Simulated Annealing (SA) algorithm. …”
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13
Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots
Published 2006“…This research explores a new approach of using a multi-objective evolutionary algorithm (MOEA) to evolve robot controllers in performing phototaxis tasks while avoiding obstacles in a simulated 30 physics environment, to overcome problems involving more than one objective, where these objectives usually trade-off among each other and are expressed in different units. …”
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14
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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15
Three Approaches to Solve Combinatorial Optimization Problems using Simulated Kalman Filter
Published 2016“…A set of traveling salesman problems is used to evaluate the performance of the proposed algorithms.…”
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16
Liquid Flow Enhancement using Natural Polymeric Additives: Effect of Concentration
Published 2016“…To evaluate the performance of the Simulated Kalman Filter algorithm, it is applied to 30 benchmark functions of CEC 2014 for real-parameter single objective optimization problems. …”
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17
Simulation of identifying shortest path walkway in library by using ant colony optimization
Published 2012“…The system is used to be error free and the algorithm can effectively solve the shortest path problem.…”
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18
Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots
Published 2006“…Bootstrap problem found during the fitness function optimization. …”
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19
Distance Evaluated Simulated Kalman Filter for Combinatorial Optimization Problems
Published 2015“…Inspired by the estimation capability of Kalman filter, we have recently introduced a novel estimation-based optimization algorithm called simulated Kalman filter (SKF). …”
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20
BSKF: Binary Simulated Kalman Filter
Published 2015“…However, the SKF is only capable to solve continuous numerical optimization problem. In order to solve combinatorial optimization problems, an extended version of SKF algorithm, which is termed as Binary SKF (BSKF), is proposed.Similar to existing approach, a mapping function is used to enable the SKF algorithm to operate in binary search space. …”
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