A greedy approximation algorithm for constructing shortest common superstrings
Theoretical Computer Science - International Symposium on Mathematical Foundations of Computer Science, Bratisl
Approximation algorithms for the shortest common superstring problem
Information and Computation
An approximation algorithm for the asymmetric travelling salesman problem with distances one and two
Information Processing Letters
The traveling salesman problem with distances one and two
Mathematics of Operations Research
Linear approximation of shortest superstrings
Journal of the ACM (JACM)
Worst-case comparison of valid inequalities for the TSP
Mathematical Programming: Series A and B
Rotations of periodic strings and short superstrings
Journal of Algorithms
\boldmath A $2\frac12$-Approximation Algorithm for Shortest Superstring
SIAM Journal on Computing
An 8/13-approximation algorithm for the asymmetric maximum TSP
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
An explicit lower bound for TSP with distances one and two
STACS'99 Proceedings of the 16th annual conference on Theoretical aspects of computer science
A new approximation algorithm for the asymmetric TSP with triangle inequality
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
An 8/13-approximation algorithm for the asymmetric maximum TSP
Journal of Algorithms
Greedy in approximation algorithms
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
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The asymmetric maximum travelling salesman problem, also known as the Taxicab Ripoff problem, is the problem of finding a maximally weighted tour in a complete asymmetric graph with non-negative weights. Interesting in its own right, this problem is also motivated by such problems such as the shortest superstring problem.We propose a polynomial time approximation algorithm for the problem with a 5/8 approximation guarantee. This (1) improves upon the approximation factors of previous results and (2) presents a simpler solution to the previously fairly involved algorithms. Our solution uses a simple LP formulation. Previous solutions where combinatorial. We make use of the LP in a novel manner and strengthen the Path-Coloring method originally proposed in [13].