Packed parts delivery problem of automotive inbound logistics with a supplier park

This paper considers a truck scheduling problem of delivering different types of parts from a supplier park to an automotive assembly plant. A supplier park is a cluster of suppliers located adjacent to an assembly plant. The parts of each type are picked up from the corresponding supplier in the park and are delivered to a buffer beside a given station of the assembly line in predetermined homogeneous packages. On a finite time horizon, the initial inventory level of each buffer at the beginning of the horizon and the quantity of each type of parts consumed on each point are given. Our problem is to make delivery schedules for capacitated trucks such that the total transportation time is minimized, and the inventory level of each buffer is within a given range at any moment within the horizon. A time-indexed integer linear programming (IP) model is proposed for the problem, and a column generation based algorithm (CGBB) is developed to solve the problem efficiently. Computational experiments based on randomly generated data and a case study based on real data collected from one of the major automotive manufacturers in China are conducted, respectively. The results show that the proposed CGBB algorithm outperforms solving the IP model by CPLEX and the greedy method used in practice. It is capable of generating high-quality solutions for the problem efficiently, and is practical to be used in daily operations.