This work demonstrates improved lower bounds for the euclidean shortest path problem, suggesting efficiency gains for A algorithms and distance queries on visibility graphs.
We consider the problem of quickly providing strong lower bounds for the planar Euclidean shortest path (ESP) problem. Such lower bounds are crucial for guiding the search in A* type approaches or for proving quality guarantees for algorithms that compute approximate solutions. Our contributions are two-fold: we show how to simplify ESP instances such that computing and storing a visibility graph becomes feasible while distances within the simplified instance are guaranteed to constitute lower bounds for the original problem instance. Furthermore we show how to precompute a space efficient data structure that allows to perform distance queries on visibility graphs within few microseconds with negligible space overhead.
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Funke et al. (2025) studied this question.
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