Greedy Conjecture for the Shortest Common Superstring Problem and its Strengthenings
<|reference_start|>Greedy Conjecture for the Shortest Common Superstring Problem and its Strengthenings: In the Shortest Common Superstring problem, one needs to find the shortest superstring for a set of strings. This problem is APX-hard, and many approximation algorithms were proposed, with the current best approximation factor of 2.466. Whereas these algorithms are technically involved, for more than thirty years the Greedy Conjecture remains unsolved, that states that the Greedy Algorithm ``take two strings with the maximum overlap; merge them; repeat'' is a 2-approximation.   This conjecture is still open, and one way to approach it is to consider its stronger version, which may make the proof easier due to the stronger premise or provide insights from its refutation. In this paper, we propose two directions to strengthen the conjecture. First, we introduce the Locally Greedy Algorithm (LGA), that selects a pair of strings not with the largest overlap but with the \emph{locally largest} overlap, that is, the largest among all pairs of strings with the same first or second string. Second, we change the quality metric: instead of length, we evaluate the solution by the number of occurrences of an arbitrary symbol.   Despite the double strengthening, we prove that LGA is a \emph{uniform} 4-approximation, that is, it always constructs a superstring with no more than four times as many occurrences of an arbitrary symbol as any other superstring. At the same time, we discover the limitations of the greedy heuristic: we show that LGA is at least 3-approximation, and the Greedy Algorithm is at least uniform 2.5-approximation. These result show that if the Greedy Conjecture is true, it is not because the Greedy Algorithm is locally greedy or is uniformly 2-approximation.<|reference_end|>
@article{nikolaev2024greedy,
    title={Greedy Conjecture for the Shortest Common Superstring Problem and its
  Strengthenings},
    author={Maksim Nikolaev},
    journal={arXiv preprint arXiv:2407.20422},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.20422},
    primaryClass={cs.DS}
}