Pickup and Delivery Problem of Automobile Outbound Logistics Considering Trans-Shipment among Distribution Centers

Abstract

This paper considers a pickup and delivery problem in automobile logistics. In the daily operations of a third-party logistics company (3PL), decisions must be made for two kinds of demands: delivering finished automobiles from an outbound warehouse to distribution centers (DCs) and transferring automobiles among the DCs according to specific customer orders. The problem is to assign a set of automobiles to a set of heterogeneous auto-carriers and deliver them to their destinations considering the outbound and transfer demands. Each automobile is assigned a value indicating its urgency level to be handled and a car type: small, medium, or large. Each of the auto-carriers has a specific number of slots with different types indicating the largest size of an automobile that can be loaded into the slot. An integer programming (IP) model is formulated for the problem to maximize the total loaded value and minimize the total transportation cost depending on the routing of the carriers. An improved adaptive large neighborhood search algorithm is developed to solve the problem efficiently, where a heuristic generates an initial solution, and a series of operators update the solution iteratively. Experimental results based on multi-scale instances show that the proposed algorithm can generate near-optimal solutions in an acceptable amount of time, and outperforms solving the IP model directly by CPLEX to a large extent. The algorithm can help 3PL companies make efficient and economical decisions in daily operations.