English

On Approximating Multi-Criteria TSP

Data Structures and Algorithms 2011-07-14 v3

Abstract

We present approximation algorithms for almost all variants of the multi-criteria traveling salesman problem (TSP). First, we devise randomized approximation algorithms for multi-criteria maximum traveling salesman problems (Max-TSP). For multi-criteria Max-STSP, where the edge weights have to be symmetric, we devise an algorithm with an approximation ratio of 2/3 - eps. For multi-criteria Max-ATSP, where the edge weights may be asymmetric, we present an algorithm with a ratio of 1/2 - eps. Our algorithms work for any fixed number k of objectives. Furthermore, we present a deterministic algorithm for bi-criteria Max-STSP that achieves an approximation ratio of 7/27. Finally, we present a randomized approximation algorithm for the asymmetric multi-criteria minimum TSP with triangle inequality Min-ATSP. This algorithm achieves a ratio of log n + eps.

Keywords

Cite

@article{arxiv.0711.2157,
  title  = {On Approximating Multi-Criteria TSP},
  author = {Bodo Manthey},
  journal= {arXiv preprint arXiv:0711.2157},
  year   = {2011}
}

Comments

Preliminary version at STACS 2009. This paper is a revised full version, where some proofs are simplified

R2 v1 2026-06-21T09:43:15.946Z