ROBUST ROUTE IDENTIFICATION USING ACO

Abstract

In this work, a study based on the ACO (Ant Colony Optimization) metaheuristic is carried out, on which different models are
proposed to study robust problems (several scenarios) taking as reference an instance of the TSP problem (Traveling Salesman
Problem). The objective was to analyze how the level of importance of the scenarios in a ROOT problem affects the performance
of the algorithms. For this, a case study was built 4 random variants of the Oliver30.tsp instance. The results revealed that the
quality of the results largely depends on the importance of the scenarios in the time windows. The best rated approaches were the
further, the more important and the less important. While considering the same importance for all scenarios proved to be a poor
strategy for robust problems.