Abstract
We present deterministic approximation algorithms for the multi-criteria maximum traveling salesman problem (Max-TSP). Our algorithms are faster and simpler than the existing randomized algorithms.
We devise algorithms for the symmetric and asymmetric multi-criteria Max-TSP that achieve ratios of 1/2k − $\varepsilon$ and 1/(4k−2) − $\varepsilon$, respectively, where k is the number of objective functions. For two objective functions, we obtain ratios of 3/8 − $\varepsilon$ and 1/4 − $\varepsilon$ for the symmetric and asymmetric TSP, respectively. Our algorithms are self-contained and do not use existing approximation schemes as black boxes.
Original language | English |
---|---|
Pages (from-to) | 2277-2285 |
Number of pages | 9 |
Journal | Discrete applied mathematics |
Volume | 160 |
Issue number | 15 |
DOIs | |
Publication status | Published - 2012 |
Keywords
- Pareto optimization
- Approximation algorithms
- Traveling Salesman Problem
- Multi-criteria optimization