Search Results - (( simulation optimization model algorithm ) OR ( program implementation from algorithm ))
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1
A multi-depot vehicle routing problem with stochastic road capacity and reduced two-stage stochastic integer linear programming models for rollout algorithm
Published 2021“…The results obtained from the resulting rollout policy with CPLEX execution during rollout are also presented to validate the reduced model and the matheuristic algorithm. …”
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2
Optimizing tree planting areas through integer programming and improved genetic algorithm
Published 2012“…To analyze the huge number of possible solutions with uncertain results manually will lead to unanswered decision of the optimal result determination. Therefore, a hybrid algorithm through an incorporation of Integer Programming and Improved Genetic Algorithm was proposed for planting lining design. …”
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3
Fast Transient Simulations From S-Parameters With Improved Reference Impedance
Published 2015“…These results respectively were obtained based on optimal reference impedance assigned in S-parameter synthesis on black box models, thus speeding up the convolution program, compared to the nominal reference impedance of 50Ω used to perform the fast transient simulation. …”
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4
Discrete-time system identification using genetic algorithm with single parent-based mating technique
Published 2024“…The methodology encompasses data acquisition, GA program development, SPM technique implementation, and simulation using MATLAB. …”
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5
Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain
Published 2020“…The Electric Transient and Analysis Program (ETAP) was used as the simulation tool, while Matrices Laboratory (MATLAB) was utilized to implement all the algorithms in this study. …”
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6
Genetic Algorithm-Based Optimization of Overcurrent Relay Coordination for Improved Protection of DFIG Operated Wind Farms
Published 2023Conference Paper -
7
Automated calibration of baseline model for energy conservation using multi-objective Evolutionary Programming (EP) / Ahmad Amiruddin Mohammad Aris
Published 2019“…The proposed co-simulation process is developed by coupling building energy simulation (BES) software, Energy Plus with multi-objective evolutionary programming (MOEP) algorithm which is implemented in Matlab using coupling software, BCVTB. …”
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8
Digital beamforming implementation of switch-beam smart antenna system by using integrated digital signal processor and field-programmable gate array
Published 2008“…In this respect, the system is firstly modeled by MATLAB software. After modeling, the algorithm is implemented in DSP. …”
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9
Deep Reinforcement Learning For Control
Published 2021“…To generate the visual simulation in the simulator, the Python programming language is employed. …”
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10
Modeling Of Electrical Distribution Networks With Particle Swarm Optimization Technique For The Improvement Of Voltage Profile And Loss Reduction
Published 2016“…Two tests, as the IEEE 34 bus test and IEEE 13 bus test are implemented. Determination of power flow was done using Open Distribution System Simulator (OpenDSS) program which is suitable for electrical distribution networks. …”
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11
Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin
Published 2014“…To enhance the robustness of the algorithm, the QIEP technique is constructed based on multiobjective model in which the multiobjective functions consist of reducing power losses, increasing maximum loadability and cost minimisation. …”
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12
Solving a multi-period inventory routing problem with stochastic unstationary demand rates
Published 2022“…A sensitivity analysis is performed on the critical parameters that influence the optimization results. The computational results show that the algorithms that implement this modified formulation can achieve a better optimization result. …”
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13
Solving a multiperiod inv entory routing problem with stochastic unstationary demand rates
Published 2022“…A sensitivity analysis is performed on the critical parameters that inf luence the optimization results. The computational results show that the algorithms that implement this modified formulation can achieve a better optimization result. …”
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14
Asset liability management model: The case of selected Islamic banks in Malaysia / Chong Hui Ling
Published 2017“…The output from the model is a set of solutions for funds allocation that minimises the asset liability performance gap for BIMB. …”
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15
Energy Management System For Controlling Series Hybrid Electric Motorcycle
Published 2016“…The characteristics identified from the dynamic programming were then used for the formulation of the energy management system. …”
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16
Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib
Published 2019“…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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17
Design of DNA fragment assembly using IWP method on application-specific integrated-circuit / Hasniliati Hassan
Published 2017“…The method proposed is to design DNA assembly algorithms in Verilog HDL and implemented it in ASIC design flow. …”
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18
Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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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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