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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
Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm
Published 2016“…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem
Published 2008“…Simulated Annealing is a global optimization technique which traverses the search space by generating neighboring solutions of the current solution. …”
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4
Opposition-based Whale Optimization Algorithm
Published 2018“…The OWOA use the Opposition-based method to enhance Whale Optimization Algorithm (WOA) performance. …”
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A multiobjective simulated Kalman filter optimization algorithm
Published 2018“…SKF is a random based optimization algorithm inspired from Kalman Filter theory. …”
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…The simulated results from the proposed DG-based SMA approach are also matched with the calculated solutions of the biogeography-based optimization (BBO) approach. …”
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7
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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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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9
On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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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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11
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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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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Angle Modulated Simulated Kalman Filter Algorithm for Combinatorial Optimization Problems
Published 2016“…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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Solution of optimal power flow using non-dominated sorting multi-objective based hybrid firefly and particle swarm optimization algorithm
Published 2020“…The efficiency of the proposed MOHFPSO technique was tested on standard IEEE 30-bus and IEEE 57-bus test systems with various conflicting objectives. Simulation results were also compared with non-dominated sorting based multi-objective particle swarm optimization (MOPSO) and different optimization algorithms reported in the current literature. …”
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Estimation-based Metaheuristics: A New Branch of Computational Intelligence
Published 2016“…By adapting the standard Kalman Filter framework, each individual agent finds an optimization solution by using a simulated measurement process that is guided by a best-so-far solution as a reference. …”
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16
A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…An intelligence strategy called quasi-oppositional based learning is incorporated into the proposed algorithm to enhance its convergence property, exploration capability, and solution optimality. …”
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Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line
Published 2010“…As the total objective values in most of problems could not be improved by simulated algorithm, it proved the well performing of proposed intelligence based genetic algorithm in reaching the near optimal solutions.…”
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Simulation for dynamic patients scheduling based on many objective optimization and coordinator
Published 2024“…Therefore, it treats PASP as a multi-objective dynamic optimization of a useful solution. NSGA-II is guaranteed 0.96 percent dominance over NSGA-II and 100 percent dominance of all other algorithms.…”
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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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20
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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