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）提出一种新型混合模型，该模型融合模糊旅行时间与循环取货（milk-run）、越库配送（cross-dock）两类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，本文提出一种基于分块矩阵的新型方法，以直观合理、高效可行的形式探索最优运输方案。所提出的基于分块矩阵的方法通过求解混合车辆路径问题推导最优运输方案，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。本文进一步提出一种扩展型生物地理学优化（biogeography-based optimization, BBO）算法：通过扩展迁移算子与变异算子、引入新型自适应变异率以及二次变异算子，以有效推导具备最优工厂满意度的运输方案。