ILS ALGORITHM FOR THE RISK-AVERSE p-HUB LOCATION PROBLEM WITH MULTIPLE ALLOCATION

This article proposes a formulation for the p-median hub location problem with multiple allocations under uncertainty conditions. A risk-averse model is proposed to deal with uncertainties in costs and demands, which uses Conditional Value at Risk (CVaR). This article also proposes an algorithm based on the Iterated Local Search (ILS) metaheuristic for the problem. Based on the performed computational experiments using scenarios generated from sets of instances in the literature, it can be seen that the ILS metaheuristic makes it possible, in these cases, to obtain good solutions with little variability and low computational time. On the other hand, computational experiments with the CPLEX solver show that the problem becomes intractable due to large runtime and excessive memory usage, even for instances with few nodes and few scenarios.