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1
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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2
Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem
Published 2008“…Genetic Algorithm gives a pool of solutions rather than just one. …”
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3
Simulated annealing algorithm for solving chambering student-case assignment problem
Published 2015“…The objective of the study is to minimize the total completion time for all students in solving the given cases.This study employed a minimum cost greedy heuristic in order to construct a feasible initial solution.The search then is preceded with a simulated annealing algorithm for further improvement of solution quality.The analysis of the obtained result has shown that the proposed simulated annealing algorithm has greatly improved the solution constructed by the minimum cost greedy heuristic. …”
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4
Simulated annealing algorithm for scheduling divisible load in large scale data grids.
Published 2009“…Many Scheduling approaches have been studied but there is no optimal solution. This paper proposes a novel Simulated Annealing (SA) algorithm for scheduling divisible load in large scale data grids. …”
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5
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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6
Cubature kalman optimizer : A novel metaheuristic algorithm for solving numerical optimization problems
Published 2023“…To further validate the performance, the proposed CKO is compared with well-known algorithms, including single-agent finite impulse response optimizer (SAFIRO), single-solution simulated Kalman filter (ssSKF), simulated Kalman filter (SKF), asynchronous simulated Kalman filter (ASKF), particle swarm optimization algorithm (PSO), genetic algorithm (GA), grey wolf optimization algorithm (GWO), and black hole algorithm (BH). …”
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7
Simulated annealing algorithm for scheduling divisible load in large scale data grids
Published 2008“…Many scheduling approaches have been studied but there is no optimal solution. This paper proposes a novel simulated annealing (SA) algorithm for scheduling divisible load in large scale data grids. …”
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8
Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions
Published 2024“…By analysing objectives and simulation outcomes, the study provides insights for system refinement. …”
Conference Paper -
9
GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE
Published 2020“…This paper will report on an initial study of the usage of Genetic Algorithm (GA) merged with Deep Neural Network based surrogate model to optimize simulation for electromagnetic structure. …”
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10
An exponential based simulated kalman filter algorithm for data-driven PID tuning in liquid slosh controller
Published 2018“…The EbSKF is compared with the original SKF algorithm. In this study, 30 independent runs are performed to record different values of the best solutions generated by the algorithms of interest. …”
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11
A study on an extended Prey-Predator algorithm
Published 2015“…In recent years, various studies have been conducted in forming new metaheuristic algorithms and modifying or improving existing algorithms to enhance the performance in optimal solution search. …”
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12
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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13
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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14
Performance evaluation of heuristic methods in solving symmetric travelling salesman problems
Published 2016“…The algorithms proposed in this study should be considered in solving symmetric travelling salesman problems.…”
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15
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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16
Synchronous-asynchronous simulated kalman filter algorithm with random switching
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An Experiment of Ant Algorithms : Case Study of Kota Kinabalu Central Town
Published 2005“…Both algorithms are compared. Simulation is used as a method in this study. …”
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18
Comparison Between Genetic Algorithm and Electromagnetism-Like Algorithm for Solving Inverse Kinematics
Published 2012“…Self developed software simulator is used to display some of these solutions at each goal position.…”
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19
A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…Furthermore, the obtained results disclose the superiority of the proposed QOMJaya algorithm over both the proposed MJaya algorithm and several previous algorithms in terms of solution optimality and feasibility.…”
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20
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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