Abstract
The k-Canadian Traveller Problem consists in finding the optimal way from a source s to a target t on an undirected weighted graph G, knowing that at most k edges are blocked. The traveller, guided by a strategy, sees an edge is blocked when he visits one of its endpoints. A major result established by Westphal is that the competitive ratio of any deterministic strategy for this problem is at least \(2k+1\). reposition and comparison strategies achieve this bound.
We refine this analysis by focusing on graphs with a maximum (s, t)-cut size \(\mu _{\text {max}}\) less than k. A strategy called detour is proposed and its competitive ratio is \(2\mu _{\text {max}}+ \sqrt{2}(k-\mu _{\text {max}}) + 1\) when \(\mu _{\text {max}}< k\) which is strictly less than \(2k+1\). Moreover, when \(\mu _{\text {max}}\ge k\), the competitive ratio of detour is \(2k+1\) and is optimal. Therefore, detour improves the competitiveness of the deterministic strategies known up to now.
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Bergé, P., Salaün, L. (2020). Improved Deterministic Strategy for the Canadian Traveller Problem Exploiting Small Max-(s, t)-Cuts. In: Bampis, E., Megow, N. (eds) Approximation and Online Algorithms. WAOA 2019. Lecture Notes in Computer Science(), vol 11926. Springer, Cham. https://doi.org/10.1007/978-3-030-39479-0_3
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DOI: https://doi.org/10.1007/978-3-030-39479-0_3
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