The Risk-averse Profitable Tour Problem

Abstract

In this paper, we tackle the risk-averse profitable tour problem with stochastic costs and risk measure objectives. This problem aims at determining a tour that maximizes the collected profit minus the total travel cost under a risk-averse perspective. We explore efficient implementations of a genetic algorithm and a tabu search method to solve the problem when the conditional value at risk and entropic risk measures are used. The computational study shows the superiority of the genetic algorithm over the tabu search on a set of instances adapted from the TSP library.