A Sim-BR algorithm for the stochastic vehicle routing problem with sustainability dimensions

Hassana Abdullahi*, Djamila Ouelhadj, Lorena Reyes-Rubiano, Angel A. Juan

*Corresponding author for this work

Research output: Contribution to conferenceAbstract


The transport sector leads to detrimental effects on the environment and social welfare. These negative impacts refer to negative externalities, which increase the logistics costs. During recent years, sustainability indicators have been proposed to quantify them. These indicators are measured in terms of economic, environmental and social dimensions. In addition, uncertainty in demand and travelling time information can have an expensive consequence on the route performance and overall costs. Travelling time uncertainty can have major consequences on driver working hours and customer time windows. Furthermore, government regulations may also restrict the number of hours of work a driver can work without breaks. Concerning the impact of demand uncertainty on the environment, an increase in fuel consumption results in an increase in emissions. Instinctively, considering that the vehicle is a conventional vehicle, the amount of fuel consumption is proportional to the amount of emissions. Thus, it is important to account for uncertainty in vehicle travelling times and demands during route planning. The social impacts considered in this paper are uncertainty around demands, which might lead to route failures and increased costs. This paper addresses the stochastic capacitated vehicle routing problem considering the sustainability dimensions. We provide a formal description of the problem and propose a stochastic optimisation model based on recourse strategies. The optimisation model considers random vehicle load and travelling time, and failure types and recourse policies are proposed. We design a simheuristic algorithm and conduct asset of extensive computational experiments. Results of the experiments offer insights into the relative impact of each objective based on its importance weight. We develop a set of scenarios offering a combination of weights and present a sensitivity analysis to measure the impacts of the sustainability indicators and quantify the trade-offs among the dimensions
Original languageEnglish
Number of pages1
Publication statusPublished - 4 Sept 2019
EventOR61 Annual Conference - University of Kent, Canterbury, United Kingdom
Duration: 3 Sept 20195 Sept 2019


ConferenceOR61 Annual Conference
Country/TerritoryUnited Kingdom


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