Robust policies for location-transportation problems with integer transshipment



In this presentation, we are looking at Location-Transportation problems with uncertain demand from the Robust Optimization perspective. The goal is to select locations of the warehouses and determine their stock levels considering the optimal strategy to satisfy the demand of customers. This type of problems has been studied extensively in the literature. One of the main, and important, difference between our problem and the ones in the literature is in the quantity of the transshipment between warehouses and the customers. In this presentation, we consider the integer transshipments. Such a problem can be encountered by spare-part suppliers or the emergency departments. As an example, the emergency departments need to know where and how many ambulances and fire engines should be located to minimize the traveling time if an emergency occurs.

In the first part of the presentations, we show for some cases how we can reformulate the multi-stage robust Location-Transportation problem into a deterministic one, and solve it exactly. In a general case, there is no efficient algorithm to solve our problem, so we propose, in the second part of the talk, two new methods to approximate it. The numerical experiments will show the efficiency of our methods.

Registration to Remy Spliet, is required for availability of lunch.