Reyes-Rubiano, Lorena SilvanaFerone, DanieleJuan Pérez, Ángel AlejandroFaulín Fajardo, Javier2020-02-182020-02-1820191696-228110.2436/20.8080.02.77https://academica-e.unavarra.es/handle/2454/36261Green transportation is becoming relevant in the context of smart cities, where the use of electric vehicles represents a promising strategy to support sustainability policies. However the use of electric vehicles shows some drawbacks as well, such as their limited driving-range capacity. This paper analyses a realistic vehicle routing problem in which both driving-range constraints and stochastic travel times are considered. Thus, the main goal is to minimize the expected time-based cost required to complete the freight distribution plan. In order to design reliable routing plans, a simheuristic algorithm is proposed. It combines Monte Carlo simulation with a multi-start metaheuristic, which also employs biased-randomization techniques. By including simulation, simheuristics extend the capabilities of metaheuristics to deal with stochastic problems. A series of computational experiments are performed to test our solving approach as well as to analyse the effect of uncertainty on the routing plans.22 p.application/pdfengCreative Commons Attribution-NonCommercial-NoDerivs 3.0 Spain (CC BY-NC-ND 3.0 ES)Vehicle routing problemElectric vehiclesGreen transport and logisticsSmart citiesSimheuristicsBiased-randomized heuristicsinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccess