Search Results - (( simulation optimization based algorithm ) OR ( parameter generation based algorithm ))
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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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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Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm
Published 2018“…In line with the emerging field called Search based Software Engineering, many recently developed t-way strategies have adopted meta-heuristic algorithms as the basis of their implementations such as Simulated Annealing, Genetic Algorithm, Ant Colony Optimization Algorithm, Particle Swarm Optimization, Harmony Search and Cuckoo Search, owing their superior performance in term of test size reduction as compared to general computational based strategies, such as General t-way, Test Vector Generator, In Parameter Order General, Jenny, and Automatic Efficient Test Generator. …”
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Thesis -
4
Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling
Published 2022“…Friedman test using GRG metric shows significant better performance (p-values<0.05) for PACS algorithm compared to benchmark algorithms. The proposed models and algorithm can be used to solve the multi-objective GMS problem while the new parameters’ values can be used to obtain optimal or near optimal maintenance scheduling of generators. …”
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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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Final Year Project -
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A multiobjective simulated Kalman filter optimization algorithm
Published 2018“…This paper presents a new multiobjective type optimization algorithm known as a Multiobjective Optimization Simulated Kalman Filter (MOSKF). …”
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A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
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DESIGN OPTIMIZATION OF A BLDC MOTOR BY GENETIC ALGORITHM AND SIMULATED ANNEALING
Published 2007“…Single and multi-objective functions of the motor are derived based on the steady state mathematical model. A constrained optimization on the objective function is performed using Genetic Algorithm (GA) and Simulated Annealing (SA), and optimal parameters are obtained. …”
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A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites
Published 2019“…Many test data generation strategies based on meta-heuristic algorithms such as Simulated Annealing (SA), Tabu Search (TS), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search (HS), Cuckoo Search (CS), Bat Algorithm (BA) and Bees Algorithm have been developed in recent years. …”
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Design optimization of a bldc motor by genetic algorithm and simulated annealing
Published 2007“…Single and multi-objective functions of the motor are derived based on the steady state mathematical model. A constrained optimization on the objective function is performed using Genetic Algorithm (GA) and Simulated Annealing (SA), and optimal parameters are obtained. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Afterward, a genetic algorithm-based optimization framework was designed to improve the interpretability and accuracy of the proposed fuzzy-tabu controller by optimizing the parameters of the FLC and also some of the planner’s parameters in order to improve the quality of the generated paths and runtimes of the planner and also to decrease the variation of the results in different runs of the planner. …”
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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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Modelling of multi-robot system for search and rescue
Published 2023“…In this project, this sensor-based algorithm is known as the Obstacle Avoidance Algorithm. …”
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Final Year Project / Dissertation / Thesis -
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS
Published 2017“…Simulation results support this idea over randomly and manually generated parameters. © 2016 Elsevier B.V.…”
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Power system stabilizer optimization using BBO algorithm for a better damping of rotor oscillations owing to small disturbances
Published 2023“…A relative comparative study is conducted between the algorithms such as BBO, particle swarm optimization (PSO) and the adaptation law based PSS on SMIB. …”
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Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm
Published 2018“…In order to overcome this limitation in an ELM-based IT2FLS, artificial bee colony optimization algorithm is utilized to obtain its antecedent parts parameters. …”
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Metaheuristic optimization of perovskite solar cell using hybrid L₃₂ Taguchi DoE-based genetic algorithm
Published 2024“…The proposed approach is realized using Solar Cell Capacitance Simulator (SCAPS-1D) software incorporated with a hybrid L32 Taguchi DoE-based Genetic Algorithm. …”
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