The vehicle routing problem with driver scheduling
研究在司机可用性约束下规划配送路线和排班的问题，提出基于迭代局部搜索的启发式算法，发现考虑司机可用性可显著降低成本并减少外包需求。
This paper addresses the vehicle routing problem with driver scheduling, which involves planning delivery routes while assigning work shifts to drivers whose individual availability must be respected. The problem extends the classical vehicle routing problem by incorporating driver availability, reflecting a growing operational concern in the logistics sector marked by persistent labor shortages and an increased need for flexible work arrangements. A mathematical model is developed to minimize total operational costs, including travel, driver shift, and outsourcing costs when some deliveries are assigned to third-party logistics providers. To handle large instances efficiently, a heuristic based on the Iterated Local Search algorithm is proposed. The algorithm integrates route optimization and driver scheduling decisions within a single framework. Computational experiments show that accounting for driver availability results in significant cost reductions and operational improvements. Even modest increases in driver availability significantly decrease the need for outsourcing, while full-day availability yields only marginal additional savings. These results offer practical managerial insights for logistics planners seeking to create a balance between operational efficiency and workforce constraints, as well as driver well-being.