Solving a Supply Chain Optimization Problem Collaboratively

We propose a novel algorithmic framework to solve an integrated planning and scheduling problem in supply chain management. This problem involves the integration of an inventory management problem and the vehicle routing problem with time windows, both of which are known to be NP-hard. Under this framework, algorithms that solve the underlying sub-problems collaborate rigorously yet in a computationally efficient manner to arrive at a good solution. We will then present two algorithms to solve the inventory management problem: a complete mathematical model integrating integer programming with constraint programming, and an incomplete algorithm based on tabu search. We present experimental results based on extended Solomon benchmark vehicle routing problems.