Search Results - (( simulation optimization using algorithm ) OR ( loading optimisation search algorithm ))
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Effective method for optimal allocation of distributed generation units in meshed electric power systems
Published 2011“…This effectively overcomes the premature convergence problem of the simple genetic algorithm (SGA). The results obtained on IEEE 6-bus and 30-bus test systems with the proposed method are evaluated with the simulation results of the classical grid search algorithm, which confirm its robustness and accuracy. …”
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Chaotic mutation immune evolutionary programming for photovoltaic planning in power system / Sharifah Azma Syed Mustaffa
Published 2020“…The second objective is to determine the location and sizing of multi-unit DGPV for single-objective problem using CMIEP. The element of chaotic local search is also integrated into the algorithm for better performance. …”
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Efficient task scheduling strategies using symbiotic organisms search algorithm for cloud computing environment
Published 2022“…Recently, a nature-inspired metaheuristic known as Symbiotic Organisms Search (SOS) optimisation algorithm was proposed. …”
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Novel techniques for voltage stability assessment and improvement in power system / Ismail Musirin.
Published 2004“…A new Evolutionary programming (EP) based acceleration search algorithm was developed to accelerate the process in estimating maximum load ability in a power system. …”
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Tap Settings Optimization in Power Systems: Economic Efficiency Enhancement Through Cuckoo Search Algorithm While Ensuring Voltage Stability
Published 2024Subjects: “…cuckoo search algorithm…”
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Variable Neighbourhood Search Algorithm for Vehicle Routing Problem with Backhaul
Published 2023“…Thus, a heuristic approach based on the Variable Neighbourhood Search (VNS) is proposed. In this research, 22 sets of benchmark instances introduced by Goetschalckx and Jacobs-Blecha are used to test the efficiency and effectiveness of the proposed algorithm. …”
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Cuckoo optimised 2DOF controllers for stabilising the frequency changes in restructured power system with wind-hydro units
Published 2021“…In this work, proportional-integral (PI), proportional-integral derivative (PID), and 2-degree of freedom PID (2-DOF-PID) controllers are proposed to stabilise the variations in the system parameters at distinct loading conditions. Different types of metaheuristic optimisation methods like teaching–learning-based optimisation (TLBO) and cuckoo search algorithms are suggested to acquire the optimal gain values of the proposed controllers. …”
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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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Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems
Published 2022“…In this case, the effectiveness and reliability of RMS is increase by combining the simulation with the optimization algorithm.…”
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A discrete simulated kalman filter optimizer for combinatorial optimization problems
Published 2022“…However, these extensions may result in increased execution times for the algorithm. In this research, a new combinatorial algorithm named discrete simulated Kalman filter optimizer (DSKFO) is proposed to solve combinatorial optimization problem. …”
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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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Unit commitment in power system using multi-agent evolutionary programming incorporating priority listing optimisation technique / Muhammad Nazree Che Othman
Published 2013“…In the proposed technique, deterministic PL technique was first applied to produce a population of initial solutions. The search process then being refined using heuristic EP-based algorithm with multi-agent approach to produce the final solution. …”
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Ant colony optimization for rule induction with simulated annealing for terms selection
Published 2012“…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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Optimization of turning parameters using genetic algorithm method
Published 2008“…The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.…”
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Undergraduates Project Papers -
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The Hybrid of WOABAT-IFDO Optimization Algorithm and Its Application in Crowd Evacuation Simulation
Published 2023“…This paper proposes a new hybrid of nature inspired optimization algorithm (IFDO-WOABAT) based on the latest optimization algorithm namely Improved Fitness Dependent Optimization (IFDO) with Whale-Bat Optimization algorithm (WOABAT). …”
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Asynchronous simulated kalman filter optimization algorithm
Published 2018“…Simulated Kalman filter (SKF) is an optimization algorithm which is inspired by Kalman filtering method. …”
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Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage
Published 2019“…Simulated Kalman Filter (SKF) is a population based optimization algorithm inspired by the Kalman filtering method. …”
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Predictive-reactive job shop scheduling for flexible production systems with the combination of optimization and simulation based algorithm
Published 2020“…The predictive part determines the feasible schedule to be used for a flow shop which is generated using a combination of rule-based simulation and optimization: first, using the optimization algorithm to compute a rough plan, followed by using a rule based simulation system to locally fine tune the plan to obtain the final schedule. …”
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