Block-matrix-based approach for the hybrid vehicle routing problem with fuzzy travel time and transportation type selection

In this study, we propose a novel hybrid model for the vehicle routing problem that combines fuzzy travel time and transportation type selection between milk-run and cross-dock strategies to derive an optimal transportation plan. Furthermore, we present a novel block-matrix-based approach for the hybrid model to explore optimal transportation plans in an intuitive, reasonable, effective, and efficient form. The proposed block-matrix-based approach derives an optimal transportation plan by solving a hybrid vehicle routing problem that considers not only fuzzy travel time, but also transportation type selection between milk-run and cross-dock strategies. An extended biogeography-based optimization (BBO) algorithm is proposed to effectively derive a transportation plan with the optimal degree of plant satisfaction by extending the operators of migration and mutation, and introducing a novel self-adaptive mutation rate, as well as a secondary mutation operator.

本研究针对车辆路径问题（vehicle routing problem）提出一种新颖的混合模型，该模型结合模糊旅行时间与循环取货（milk-run）、越库配送（cross-dock）两种策略间的运输类型选择，以推导最优运输方案。此外，针对该混合模型，本文提出一种新颖的基于分块矩阵（block-matrix）的方法，能够以直观、合理、有效且高效的形式探索最优运输方案。所提基于分块矩阵的方法通过求解混合车辆路径问题来推导最优运输方案，该问题不仅考量模糊旅行时间，还兼顾循环取货与越库配送策略间的运输类型选择。本文提出一种扩展型生物地理学优化算法（biogeography-based optimization, BBO），通过拓展迁移与变异算子、引入新颖的自适应变异率以及二次变异算子，可有效推导得到具备最优工厂满意度的运输方案。