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    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/6913

    Título
    A parallel programming approach to the solution of the location-inventory and multi-echelon routing problem in the humanitarian supply chain
    Autor
    Angarita Monroy, Andrés Guillermo
    Lamos Díaz, Henry
    Publicado en
    R-Evolucionando el transporte
    Editorial
    Universidad de Burgos. Servicio de Publicaciones e Imagen Institucional
    Fecha de publicación
    2021-07
    ISBN
    978-84-18465-12-3
    DOI
    10.36443/10259/6913
    Descripción
    Trabajo presentado en: R-Evolucionando el transporte, XIV Congreso de Ingeniería del Transporte (CIT 2021), realizado en modalidad online los días 6, 7 y 8 de julio de 2021, organizado por la Universidad de Burgos
    Resumen
    Disasters around the world are becoming more frequent, diverse, complex and extremely challenging, causing millions of casualties and affecting both human development and available resources. Consequently, the present study addresses a multi-objective location, inventory and multi-scale routing (2E-LIRP) problem, which supports comprehensive decision making, so that the logistics network designer and manager can obtain adequate strategic planning in the face of uncertainty and the negative impact that an adverse event can generate. Moreover, the problem is formulated as an integer linear programming model, having as main objectives to minimize private logistics costs and maximize the welfare of the affected areas, considering dynamic demand, multiple products and heterogeneous fleet. Due to the computational complexity associated with the model, a new solution approach is proposed, based on the design of evolutionary metaheuristic algorithms; the first one, known as Non-dominated Sorting Genetic Algorithm version II (NSGA-II), the second one, Strength Pareto Evolutionary Algorithm version II (SPEA-II) and the third one, called Genetic Algorithm (GA), programmed in parallel and executed individually under a cooperative environment. Finally, the experimentation carried out on a test set, composed of twenty instances of varying complexity, allows inferring that the parallel-cooperative and purely parallel approach applied to NSGA-II, substantially improves the processing times and the number of non-dominated solutions, if compared to the results obtained by SPEA-II, designed under identical conditions. Moreover, by building a GA with these same characteristics, it improves up to 50% of the solutions, in terms of social costs (logistic and humanitarian costs), with computation times similar to its sequential counterpart.
    Palabras clave
    Logística
    Logistics
    Operaciones
    Operations
    Materia
    Transportes
    Transportation
    Asistencia social
    Human services
    URI
    http://hdl.handle.net/10259/6913
    Versión del editor
    https://doi.org/10.36443/9788418465123
    Relacionado con
    http://hdl.handle.net/10259/6490
    Aparece en las colecciones
    • Congreso de Ingeniería del Transporte CIT 2021 (14º. 2021. Burgos)
    Ficheros en este ítem
    Nombre:
    Angarita_CIT2021_1115-1138.pdf
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    394.6Kb
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