RT info:eu-repo/semantics/conferenceObject
T1 A parallel programming approach to the solution of the location-inventory and multi-echelon routing problem in the humanitarian supply chain
A1 Angarita Monroy, Andrés Guillermo
A1 Lamos Díaz, Henry
K1 Logística
K1 Logistics
K1 Operaciones
K1 Operations
K1 Transportes
K1 Transportation
K1 Asistencia social
K1 Human services
AB Disasters around the world are becoming more frequent, diverse, complex and extremelychallenging, causing millions of casualties and affecting both human development andavailable resources. Consequently, the present study addresses a multi-objective location,inventory and multi-scale routing (2E-LIRP) problem, which supports comprehensivedecision making, so that the logistics network designer and manager can obtain adequatestrategic planning in the face of uncertainty and the negative impact that an adverse eventcan generate.Moreover, the problem is formulated as an integer linear programming model, having asmain objectives to minimize private logistics costs and maximize the welfare of theaffected areas, considering dynamic demand, multiple products and heterogeneous fleet.Due to the computational complexity associated with the model, a new solution approachis proposed, based on the design of evolutionary metaheuristic algorithms; the first one,known as Non-dominated Sorting Genetic Algorithm version II (NSGA-II), the secondone, Strength Pareto Evolutionary Algorithm version II (SPEA-II) and the third one, calledGenetic Algorithm (GA), programmed in parallel and executed individually under acooperative environment. Finally, the experimentation carried out on a test set, composedof twenty instances of varying complexity, allows inferring that the parallel-cooperativeand purely parallel approach applied to NSGA-II, substantially improves the processingtimes and the number of non-dominated solutions, if compared to the results obtained bySPEA-II, designed under identical conditions. Moreover, by building a GA with thesesame characteristics, it improves up to 50% of the solutions, in terms of social costs(logistic and humanitarian costs), with computation times similar to its sequentialcounterpart.
PB Universidad de Burgos. Servicio de Publicaciones e Imagen Institucional
SN 978-84-18465-12-3
YR 2021
FD 2021-07
LK http://hdl.handle.net/10259/6913
UL http://hdl.handle.net/10259/6913
LA eng
NO 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
DS Repositorio Institucional de la Universidad de Burgos
RD 24-nov-2024