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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，该模型融合模糊出行时间与循环取货（milk-run）、越库配送（cross-dock）两类策略间的运输类型选择机制，以生成最优运输方案。此外，针对该混合模型，我们提出一种基于分块矩阵（block-matrix）的新型方法，能够以直观合理、高效且有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得到最优运输方案，该问题同时考量模糊出行时间，以及循环取货与越库配送策略间的运输类型选择。针对迁移与变异算子进行拓展，引入新型自适应变异率及二次变异算子，本文提出一种拓展型生物地理学优化（biogeography-based optimization, BBO）算法，可有效求解得到具备最优工厂满意度的运输方案。