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DOI: 10.4230/OASIcs.ATMOS.2025.13

Multi-Criteria Route Planning with Little Regret

Authors: Carina Truschel and Sabine Storandt

Published in: OASIcs, Volume 137, 25th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2025)

Abstract

Multi-criteria route planning arises naturally in real-world navigation scenarios where users care about more than just one objective - such as minimizing travel time while also avoiding steep inclines or unpaved surfaces or toll routes. To capture the possible trade-offs between competing criteria, many algorithms compute the set of Pareto-optimal paths, which are paths that are not dominated by others with respect to the considered cost vectors. However, the number of Pareto-optimal paths can grow exponentially with the size of the input graph. This leads to significant computational overhead and results in large output sets that overwhelm users with too many alternatives. In this work, we present a technique based on the notion of regret minimization that efficiently filters the Pareto set during or after the search to a subset of specified size. Regret minimizing algorithms identify such a representative solution subset by considering how any possible user values any subset with respect to the objectives. We prove that regret-based filtering provides us with quality guarantees for the two main query types that are considered in the context of multi-criteria route planning, namely constrained shortest path queries and personalized path queries. Furthermore, we design a novel regret minimization algorithm that works for any number of criteria, is easy to implement and produces solutions with much smaller regret value than the most commonly used baseline algorithm. We carefully describe how to incorporate our regret minimization algorithm into existing route planning techniques to drastically reduce their running times and space consumption, while still returning paths that are close-to-optimal.

Cite as

Carina Truschel and Sabine Storandt. Multi-Criteria Route Planning with Little Regret. In 25th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2025). Open Access Series in Informatics (OASIcs), Volume 137, pp. 13:1-13:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{truschel_et_al:OASIcs.ATMOS.2025.13,
  author =	{Truschel, Carina and Storandt, Sabine},
  title =	{{Multi-Criteria Route Planning with Little Regret}},
  booktitle =	{25th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2025)},
  pages =	{13:1--13:20},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-404-8},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{137},
  editor =	{Sauer, Jonas and Schmidt, Marie},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2025.13},
  URN =		{urn:nbn:de:0030-drops-247698},
  doi =		{10.4230/OASIcs.ATMOS.2025.13},
  annote =	{Keywords: Pareto-optimality, Regret minimization, Contraction Hierarchies}
}

Document

DOI: 10.4230/LIPIcs.ESA.2025.42

(Multivariate) k-SUM as Barrier to Succinct Computation

Authors: Geri Gokaj, Marvin Künnemann, Sabine Storandt, and Carina Truschel

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract

How does the time complexity of a problem change when the input is given succinctly rather than explicitly? We study this question for several geometric problems defined on a set X of N points in ℤ^d. As succinct representation, we choose a sumset (or Minkowski sum) representation: Instead of receiving X explicitly, we are given sets A,B of n points that define X as A+B = {a+b∣ a ∈ A,b ∈ B}. We investigate the fine-grained complexity of this succinct version for several Õ(N)-time computable geometric primitives. Remarkably, we can tie their complexity tightly to the complexity of corresponding k-SUM problems. Specifically, we introduce as All-ints 3-SUM(n,n,k) the following multivariate, multi-output variant of 3-SUM: given sets A,B of size n and set C of size k, determine for all c ∈ C whether there are a ∈ A and b ∈ B with a+b = c. We obtain the following results: 1) Succinct closest L_∞-pair requires time N^{1-o(1)} under the 3-SUM hypothesis, while succinct furthest L_∞-pair can be solved in time Õ(n). 2) Succinct bichromatic closest L_∞-Pair requires time N^{1-o(1)} iff the 4-SUM hypothesis holds. 3) The following problems are fine-grained equivalent to All-ints 3-SUM(n,n,k): succinct skyline computation in 2D with output size k and succinct batched orthogonal range search with k given ranges. This establishes conditionally tight Õ(min{nk, N})-time algorithms for these problems. We obtain further connections with All-ints 3-SUM(n,n,k) for succinctly computing independent sets in unit interval graphs. Thus, (Multivariate) k-SUM problems precisely capture the barrier for enabling sumset-succinct computation for various geometric primitives.

Cite as

Geri Gokaj, Marvin Künnemann, Sabine Storandt, and Carina Truschel. (Multivariate) k-SUM as Barrier to Succinct Computation. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 42:1-42:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{gokaj_et_al:LIPIcs.ESA.2025.42,
  author =	{Gokaj, Geri and K\"{u}nnemann, Marvin and Storandt, Sabine and Truschel, Carina},
  title =	{{(Multivariate) k-SUM as Barrier to Succinct Computation}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{42:1--42:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.42},
  URN =		{urn:nbn:de:0030-drops-245101},
  doi =		{10.4230/LIPIcs.ESA.2025.42},
  annote =	{Keywords: Fine-grained complexity theory, sumsets, additive combinatorics, succinct inputs, computational geometry}
}

Document

DOI: 10.4230/LIPIcs.ESA.2023.60

Pareto Sums of Pareto Sets

Authors: Demian Hespe, Peter Sanders, Sabine Storandt, and Carina Truschel

Published in: LIPIcs, Volume 274, 31st Annual European Symposium on Algorithms (ESA 2023)

Abstract

In bi-criteria optimization problems, the goal is typically to compute the set of Pareto-optimal solutions. Many algorithms for these types of problems rely on efficient merging or combining of partial solutions and filtering of dominated solutions in the resulting sets. In this paper, we consider the task of computing the Pareto sum of two given Pareto sets A, B of size n. The Pareto sum contains all non-dominated points of the Minkowski sum M = {a+b|a ∈ A, b ∈ B}. Since the Minkowski sum has a size of n², but the Pareto sum C can be much smaller, the goal is to compute C without having to compute and store all of M. We present several new algorithms for efficient Pareto sum computation, including an output-sensitive one with a running time of 𝒪(n log n + nk) and a space consumption of 𝒪(n+k) for k = |C|. We also describe suitable engineering techniques to improve the practical running times of our algorithms and provide a comparative experimental study. As one showcase application, we consider preprocessing-based methods for bi-criteria route planning in road networks. Pareto sum computation is a frequent task in the preprocessing phase. We show that using our algorithms with an output-sensitive space consumption allows to tackle larger instances and reduces the preprocessing time compared to algorithms that fully store M.

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Demian Hespe, Peter Sanders, Sabine Storandt, and Carina Truschel. Pareto Sums of Pareto Sets. In 31st Annual European Symposium on Algorithms (ESA 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 274, pp. 60:1-60:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{hespe_et_al:LIPIcs.ESA.2023.60,
  author =	{Hespe, Demian and Sanders, Peter and Storandt, Sabine and Truschel, Carina},
  title =	{{Pareto Sums of Pareto Sets}},
  booktitle =	{31st Annual European Symposium on Algorithms (ESA 2023)},
  pages =	{60:1--60:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-295-2},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{274},
  editor =	{G{\o}rtz, Inge Li and Farach-Colton, Martin and Puglisi, Simon J. and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2023.60},
  URN =		{urn:nbn:de:0030-drops-187132},
  doi =		{10.4230/LIPIcs.ESA.2023.60},
  annote =	{Keywords: Minkowski sum, Skyline, Successive Algorithm}
}

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Documents authored by Truschel, Carina

Multi-Criteria Route Planning with Little Regret

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(Multivariate) k-SUM as Barrier to Succinct Computation

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Pareto Sums of Pareto Sets

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