A HYBRID ALGORITHM FOR THE UNCERTAIN INVERSE p-MEDIAN LOCATION PROBLEM

Abstract

In this paper, we investigate the inverse p-median location problem with variable edge lengths and variable vertex weights on networks in which the vertex weights and modification costs are the independent uncertain variables. We propose a model for the uncertain inverse p-median location problem with tail value at risk objective. Then, we show that it is NP-hard. Therefore, a hybrid particle swarm optimization algorithm is presented to obtain the approximate optimal solution of the proposed model. The algorithm contains expected value simulation and tail value at risk simulation.