The technician routing and scheduling problem with conventional and electric vehicle
Résumé
Motivated by stricter environmental regulations, government incentives, branding opportunities, and potential cost reductions, companies are replacing their conventional vehicles (CVs) with electric vehicles (EVs). However, due to financial and operational restrictions, these fleet transitions usually occur in several stages. This introduces new operational challenges, because most existing fleet management and routing tools are not designed to handle hybrid fleets of CVs and EVs. In this paper, we study a problem arising in the daily operations of telecommunication companies, public utilities, home healthcare providers, and other businesses: the technician routing and scheduling problem with conventional and electric vehicles (TRSP-CEV). To solve this problem we propose a two-phase parallel matheuristic. In the first phase the matheuristic decomposes the problem into several vehicle routing problems with time windows, and it solves these problems (in parallel) using a greedy randomized adaptive search procedure (GRASP). At the end of each GRASP iteration, the routes making up the local optimum are stored in long-term memory. In the second phase, the method uses the stored routes to find a TRSP-CEV solution. We discuss computational experiments on industrial instances provided by a French utility. We provide managerial insight into the impact of the proportion of EVs in the fleet on metrics such as the number of routes, the total operational cost, and the CO2 emissions. Additionally, we present state-of-the-art results for the closely related electric fleet size and mix vehicle routing problem with time windows and recharging stations.
Domaines
Recherche opérationnelle [math.OC]
Origine : Fichiers produits par l'(les) auteur(s)
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