Abstract
We present approximation algorithms for almost all variants of the multicriteria traveling salesman problem (TSP).
First, we devise randomized approximation algorithms for multicriteria maximum traveling salesman problems (Max-TSP). For multicriteria Max-STSP where the edge weights have to be symmetric, we devise an algorithm with an approximation ratio of 2/3 $-\varepsilon.$ For multicriteria Max-ATSP where the edge weights may be asymmetric, we present an algorithm with a ratio of 1/2 $-\varepsilon.$ Our algorithms work for any fixed number k of objectives. Furthermore, we present a deterministic algorithm for bicriteria Max-STSP that achieves an approximation ratio of 7/27.
Finally, we present a randomized approximation algorithm for the asymmetric multicriteria minimum TSP with triangle inequality (Min-ATSP). This algorithm achieves a ratio of log $n + \varepsilon.$
Original language | Undefined |
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Article number | 17 |
Pages (from-to) | 17:1-17:18 |
Number of pages | 18 |
Journal | ACM transactions on algorithms |
Volume | 8 |
Issue number | 2 |
DOIs | |
Publication status | Published - Apr 2012 |
Keywords
- EWI-20668
- Approximation algorithms
- Multi-objective optimization
- IR-80244
- Pareto curves
- METIS-289629
- Traveling Salesman Problem