Capacitated Vehicle Routing Problem with 2-dimensional Loading Constraints Study based on Improved Estimation of Distribution Algorithm

The capacitated vehicle routing problem with 2dimensional loading constraints ($\mathbf{2 L}-\mathbf{C V R P}$) integrates aspects of both the vehicle routing problem and the two-dimensional bin packing problem. To address this challenge, an Improved Estimation of Distribution Algorithm (IEDA) is proposed in this paper. The IEDA employs a probability model which is designed to characterize the distribution of the solution space. Specifically, for the packing subproblem, a skyline-based bin packing algorithm is utilized to assess the feasibility of packing items for a given route. For the routing subproblem, the probability matrix generated by IEDA guides the global search. Furthermore, to improve local exploitation capabilities, a variable neighborhood search operator is integrated into the IEDA algorithm, enabling a finegrained search. The simulation results indicate that the proposed IEDA outperforms the classic baseline algorithms across different categories of benchmark instances.