Constraint-Based Local Search for Inventory Control Under Stochastic Demand and Lead Time

General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact [email protected] providing details, and we will remove access to the work immediately and investigate your claim. In this paper, we address the general multi-period production/inventory problem with non-stationary stochastic demand and supplier lead time under service-level constraints. A replenishment cycle policy is modeled. We propose two hybrid algorithms that blend Constraint Programming and Local Search for computing near-optimal policy parameters. Both the algorithms rely on a coordinate descent Local Search strategy, what differs is the way this strategy interacts with the Constraint Programming solver. These two heuristics are, firstly, compared for small instances against an existing optimal solution method. Secondly, they are tested and compared with each other in terms of solution quality and run time on a set of larger instances that are intractable for the exact approach. Our numerical experiments show the effectiveness of our methods.