A Confidence-based Bilevel Memetic Algorithm with Adaptive Selection Scheme for Capacitated Electric Vehicle Routing Problem

Due to the advancements in electric vehicles, a new variant of the Vehicle Routing Problem (VRP) has emerged into what is known as the Capacitated Electric Vehicle Routing Problem (CEVRP). CEVRP is characterised by longer charging time, restrictive cruising range, and challenges posed by the scarcity of charging stations. In response to the new characteristics and challenges brought by CEVRP, we introduce a Confidence-based Bilevel Memetic Algorithm (CBMA). Furthermore, an adaptive selection scheme is introduced, which can dynamically adjust the algorithm's convergence, i.e., accelerating convergence in the early stage while maintaining exploration capability as convergence slows down. Experimental results demonstrate that the proposed algorithm outperforms existing algorithms and breaks the records of six previously best-known solutions in the IEEE WCCI-2020 benchmark.