New Approximation-Based Local Search Algorithms for the Probabilistic Traveling Salesman Problem

摘要

In this paper we present new local search algorithms for the Probabilistic Traveling Salesman Problem (PTSP) using sampling and ad-hoc approximation. These algorithms improve both runtime and solution quality of state-of-the-art local search algorithms for the PTSP.