Optimization of vendor-managed inventory systems in a rolling horizon framework

This paper aims at designing a dynamic VMI system. In this system, the entire supply chain performance is optimized in terms of production planning at vendor’s site, distribution strategy, and inventory management at manufacturer’s site. We also explore some of the complications involved in setting up such a system. The VMI system is modeled as a mixed-integer linear program (MILP) using discrete-time representation. The mathematical representation follows the resource-task network (RTN) formulation. To address the complexity of the problem, different optimization-based solution algorithms are proposed and compared in terms of solution quality and CPU time. First, the problem is solved directly using an exact detailed model. Secondly, an iterative procedure combines a novel aggregate model with the detailed model to provide aggregate pre-matches for the detailed binary variables. Finally, a novel rolling horizon approach that simultaneously combines the aggregate and the detailed models is designed to solve the problem. The entire VMI system is tested with an illustrative example.