Efficient Approximations for Many-Visits Multiple Traveling Salesman Problems

TL;DR

This paper introduces efficient approximation algorithms for the many-visits multiple Traveling Salesman Problem, a complex variant with real-world applications like aircraft sequencing, providing high-quality solutions quickly.

Contribution

It presents novel approximation algorithms for the many-visits mTSP, extending previous work to handle multiple visits per city with guaranteed solution quality.

Findings

Algorithms achieve high-quality solutions efficiently

Applicable to real-world problems like aircraft sequencing

Significantly improve solution speed for complex mTSP variants

Abstract

A fundamental variant of the classical traveling salesman problem (TSP) is the so-called multiple TSP (mTSP), where a set of $m$ salesmen jointly visit all cities from a set of $n$ cities. The mTSP models many important real-life applications, in particular for vehicle routing problems. An extensive survey by Bektas (Omega 34(3), 2006) lists a variety of heuristic and exact solution procedures for the mTSP, which quickly solve particular problem instances. In this work we consider a further generalization of mTSP, the many-visits mTSP, where each city $v$ has a request $r(v)$ of how many times it should be visited by the salesmen. This problem opens up new real-life applications such as aircraft sequencing, while at the same time it poses several computational challenges. We provide multiple efficient approximation algorithms for important variants of the many-visits mTSP, which are guaranteed to quickly compute high-quality solutions for all problem instances.