A Tailored Meta-Heuristic for the Autonomous Electric Vehicle Routing Problem Considering the Mixed Fleet

In recent years, some phenomena such as the COVID-19 pandemic have caused autonomous vehicle (AV) to attract much attention in theoretical and applied research. This paper addresses optimization problem of a heterogeneous fleet that consists electric vehicles (AEVs) conventional (CVs) Business-to-Consumer (B2C) distribution system. The absence driver AEVs results necessity studying two factors modeling problem, namely time windows routing plan different compartments loading space AEVs. We developed mathematical model based on these properties, was NP-hard. Then we proposed hybrid algorithm, including variable neighborhood search (VNS) via structure large (LNS), VLNS algorithm. numerical shed light proficiency algorithm terms solution quality. addition, employing mixed is considered be desirable operational cost fleet. show decreases average by 57.22% compared with homogeneous