Search Results - (( simulation optimization based algorithm ) OR ( based optimization approach algorithm ))
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1
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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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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3
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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4
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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5
Multi-State Particle Swarm Optimization for Discrete Combinatorial Optimization Problem
Published 2014“…The binary-based algorithms including the binary particle swarm optimization (BPSO) algorithm are proposed to solve discrete optimization problems. …”
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Enhanced genetic algorithm optimization model for a single reservoir operation based on hydropower generation: case study of Mosul reservoir, northern Iraq
Published 2016“…The first algorithm was based on the traditional simulation of reservoir operation, whilst the second algorithm (Salg) enhanced the GAOM by changing the population values of GA through a new simulation process of reservoir operation. …”
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7
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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8
Improved opposition-based particle swarm optimization algorithm for global optimization
Published 2021“…All the observations from our simulations conclude that the proposed ASOA is superior to conventional optimizers. …”
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Predictive-reactive job shop scheduling for flexible production systems with the combination of optimization and simulation based algorithm
Published 2020“…It would be a promising approach to combine the advantages of simulation with optimization algorithm.…”
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A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application
Published 2011“…Present paper intends to provide a detailed description of a new bio-inspired Metaheuristic Algorithm. Based on the detailed study of the Drosophila, the flowchart behaviour for the algorithm, code implementation, methodologies and simulation analysis, a novel Fly Optimization Algorithm (FOA) approach is presented. …”
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A particle swarm optimization and min-max-based workflow scheduling algorithm with QoS satisfaction for service-oriented grids
Published 2017“…The algorithm selects the best scheduling solutions based on the proposed constraint-handling strategy. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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13
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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14
African Buffalo Optimization (ABO): A New Metaheuristic Algorithm
Published 2015“…The African Buffalo Optimization (A.B.0) algorithm simulates the African buffalos' behaviour by encapsulation in a mathematical model; which solves a number of discrete optimization problems using graph-based route planning, job scheduling and it extends Swarm Intelligence paradigms. …”
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15
New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…Subsequently, it is exploring into the development of random approaches based on MABSA, integrating components into others algorithm whereby Squirrel Search Algorithm (SSA), Cauchy Mutation (CM) approach, and Doppler Effect (DE) phenomenon. …”
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16
Optimization of turning parameters using genetic algorithm method
Published 2008“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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Opposition- based simulated kalman filters and their application in system identification
Published 2017“…Among the various kinds of optimization algorithms, Simulated Kalman Filter (SKF) is a new population-based optimization algorithm inspired by the estimation capability of Kalman Filter. …”
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18
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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Adaptable algorithms for performance optimization of dynamic batch manufacturing processes
Published 2018“…Performance analyses are presented to validate how significant of the dynamic optimization based on the product molarity surpasses the existing conventional prescribed temperature approach. …”
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20
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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