Phase transitions of Traveling Salesperson problems solved with linear programming and cutting planes

The Traveling Salesperson problem asks for the shortest cyclic tour visiting a set of cities given their pairwise distances and belongs to the NP-hard complexity class, which means that with all known algorithms in the worst case instances are not solvable in polynomial time, i.e., the problem is hard. However, this does not mean that there are not subsets of the problem which are easy to solve. To examine numerically transitions from an easy to a hard phase, a random ensemble of cities in the Euclidean plane, given a parameter σ, which governs the hardness, is introduced. Here, a linear programming approach together with suitable cutting planes is applied. Such algorithms operate outside the space of feasible solutions and are often used in practical applications but rarely studied in physics so far. We observe several transitions. To characterize these transitions, scaling assumptions from continuous phase transitions are applied.