In modern society, sustainable transportation practices in smart cities are becoming increasingly important for both companies and citizens. These practices constitute a global trend, which affects multiple sectors resulting in relevant socio-economic and environmental challenges. Moreover, uncertainty plays a crucial role in transport activities; for instance, travel time may be affected by road work, the weather, or accidents, among others. This paper addresses a rich extension of the capacitated vehicle routing problem, which considers sustainability indicators (i.e., economic, environmental and social impacts) and stochastic traveling times. A simheuristic approach integrating Monte Carlo simulation into a multi-start metaheuristic is proposed to solve it. A computational experiment is carried out to validate our approach, and analyze the trade-off between sustainability dimensions and the effect of stochasticity on the solutions.
English
stochastic processes; vehicle routing; Monte Carlo methods; smart cities; socio-economic effects; freight handling; sustainable development; procesos estocásticos; ruta para vehículos; métodos Monte Carlo; ciudades inteligentes; efectos socioeconómicos; manipulación de carga; desarrollo sostenible; processos estocàstics; ruta per a vehicles; mètodes Monte Carlo; ciutats intel·ligents; efectes socioeconòmics; manipulació de càrrega; desenvolupament sostenible; Algorithms; Algorismes; Algoritmos
Winter Simulation Conference (WSC). Proceedings
Winter Simulation Conference (WSC). Proceedings, 2017
Winter Simulation Conference, Las Vegas, EUA, 03-06, desembre de 2017
https://www.informs-sim.org/wsc17papers/includes/files/279.pdf
https://ieeexplore.ieee.org/document/8248051
info:eu-repo/grantAgreement/TRA2013-48180-C3-P
info:eu-repo/grantAgreement/TRA2015-71883-REDT
info:eu-repo/grantAgreement/2016-1ES01-KA108-023465
info:eu-repo/grantAgreement/CYTED2014-515RT0489
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