Abstract
Widespread adoption of electric vehicles (EVs) is expected to accelerate in the near future, and logistics and supply chain companies are compelled to keep up with this transformation. The challenges posed by adopting EVs for delivery systems include battery capacity, driving ranges, and charging durations. Companies should address these challenges effectively to continue fulfilling customer demands on time and keep their operational costs under control. Establishing efficient EV routing plans (EVRP) that incorporate charging policies and vehicles’ technical features will make companies’ logistics operations both sustainable and competitive. Therefore, this study proposes a mathematical model for the EVRP that incorporates heterogeneous vehicles and partial re-charging policy options. The proposed model aims to identify the best delivery routes, re-charging locations, and schedules that minimize total operational costs under soft time windows and varying types of chargers. Notably, this model considers a single depot and a set of customers, each with specific demand and time windows. EVs’ energy consumption rates, charging speeds, load capacities, and battery capacities are explicitly incorporated into the routing and scheduling decisions under the proposed model. Additionally, operation cost includes three different variations: diverse operating costs for different vehicle types, functional penalty costs for unscheduled delivery times, and heterogeneous energy costs based on distance. Moreover, the usage of different charger types in charging stations is a factor that can help decrease routing times and, thus, operation costs. Our model’s use of a heterogenous fleet and different charger types makes it effective for real-life scenarios.