In this work, we consider a risk-averse maximum weighted k-club problems. It is assumed that vertices of the graph have stochastic weights whose joint distribution is known. The goal is to find the k-club of minimum risk contained in the graph. A stochastic programming framework that is based on the formalism of coherent risk measures is used to find the corresponding subgraphs. The selected re...
