Examinando por Materia "Heuristic optimization"

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  • Miniatura
    Ítem
    Economic Dispatch in Microgrids with Renewable Energy Using Interior Point Algorithm and Lineal Constrainst
    (Universidad EAFIT, 2017-04-24) Arango, Dario; Urrego, Ricardo; Rivera, Sergio; Universidad Nacional de Colombia
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    Ítem
    Energy management strategy for a solar race car including meteorologic and probabilistic variable
    (2018) Betancur Valencia, Esteban; Osorio Gómez, Gilberto
    This thesis describes the energy management strategy for racing solar cars, the racing strategy is treated as an optimal control problem with random variables and uncertain predictions. A computational model is developed for estimating the vehicle performance under specific circumstances. Two evolutionary heuristic optimization methods are implemented and tested for this case, their effectiveness, convergence and efficiency is measured and compared to exhaustive search approaches. The dependency on solar radiation is validated using the computational model with different test cases. In order to reduce the uncertainties on the solar radiation estimation, satellite images are used as inputs to image processing and machine learning techniques, their efficacy is compared. Finally, a validation case is executed and different scenarios are evaluated with the inclusion of the proposed methods, the experimental performance of a vehicle obtained using the strategy in the World Solar Challenge 2015 is exposed and compared to the predicted results from the simulation.
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    Ítem
    A variable block insertion heuristic for permutation flowshops with makespan criterion
    (Institute of Electrical and Electronics Engineers Inc., 2017-01-01) Tasgetiren M.F.; Pan Q.-K.; Kizilay D.; Velez-Gallego M.C.; Universidad EAFIT. Departamento de Ingeniería de Producción; Gestión de Producción y Logística
    This paper proposes a populated variable block insertion heuristic (PVBIH) algorithm for solving the permutation flowshop scheduling problem with the makespan criterion. The PVBIH algorithm starts with a minimum block size being equal to one. It removes a block from the current solution and inserts it into the partial solution randomly with a predetermined move size. A local search is applied to the solution found after several block moves. If the new solution generated after the local search is better than the current solution, it replaces the current solution. It retains the same block size as long as it improves. Otherwise, the block size is incremented by one and a simulated annealing-type of acceptance criterion is used to accept the new solution. This process is repeated until the block size reaches at the maximum block size. In addition, we present a randomized profile fitting heuristic with excellent results. Extensive computational results on the Taillard's well-known benchmark suite show that the proposed PVBIH algorithm substantially outperforms the differential evolution algorithm (NS-SGDE) recently proposed in the literature. © 2017 IEEE.