A Simheuristic Algorithm for the Location Routing Problem with Facility Sizing Decisions and Stochastic Demands

Location routing is a well known problem in which decisions about facility location and vehicle routing must be made. Traditionally, a fixed size or capacity is assigned to an open facility as the input parameter to the problem. However, real-world cases show that decision-makers usually have a set of size options. If this size is selected accurately according to the demand of allocated customers, then location decisions and routing activities would raise smaller cost. Nevertheless, choosing this size implies additional variables that make an already NP-hard problem even more challenging. In addition, considering stochastic demands contributes to making the optimization problem more difficult to solve. Hence, a simheuristic algorithm is proposed in this work. It combines the efficiency of metaheuristics and the capabilities of simulation to deal with uncertainty. A series of computational experiments show that our approach can efficiently deal with medium-large instances.