Abstract
An instance of the NP-hard Quadratic Shortest Path Problem (QSPP) is called linearizable iff it is equivalent to an instance of the classic Shortest Path Problem (SPP) on the same input digraph. The linearization problem for the QSPP (LinQSPP) decides whether a given QSPP instance is linearizable and determines the corresponding SPP instance in the positive case. We provide a novel linear time algorithm for the LinQSPP on acyclic digraphs which runs considerably faster than the previously best algorithm. The algorithm is based on a new insight revealing that the linearizability of the QSPP for acyclic digraphs can be seen as a local property. Our approach extends to the more general higher-order shortest path problem.
G. J. Woeginger—Deceased in April 2022.
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Notes
- 1.
We use the same notation for the path P and the set of its arcs.
- 2.
We assume that f is given as an oracle.
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This research has been supported by the Austrian Science Fund (FWF): W1230.
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Çela, E., Klinz, B., Lendl, S., Woeginger, G.J., Wulf, L. (2023). A Linear Time Algorithm for Linearizing Quadratic and Higher-Order Shortest Path Problems. In: Del Pia, A., Kaibel, V. (eds) Integer Programming and Combinatorial Optimization. IPCO 2023. Lecture Notes in Computer Science, vol 13904. Springer, Cham. https://doi.org/10.1007/978-3-031-32726-1_33
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