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Documents authored by Stiglmayr, Michael


Document
The Line-Based Dial-a-Ride Problem

Authors: Kendra Reiter, Marie Schmidt, and Michael Stiglmayr

Published in: OASIcs, Volume 123, 24th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2024)


Abstract
On-demand ridepooling systems offer flexible services pooling multiple passengers into one vehicle, complementing traditional bus services. We propose a transportation system combining the spatial aspects of a fixed sequence of bus stops with the temporal flexibility of ridepooling. In the line-based Dial-a-Ride problem (liDARP), vehicles adhere to a fixed, ordered sequence of stops in their routes, with the possibility of taking shortcuts and turning if they are empty. We propose three MILP formulations for the liDARP with a multi-objective function balancing environmental aspects with customer satisfaction, comparing them on a real-world bus line. Our experiments show that the formulation based on an Event-Based graph is the fastest, solving instances with up to 50 requests in under one second. Compared to the classical DARP, the liDARP is computationally faster, with minimal increases in total distance driven and average ride times.

Cite as

Kendra Reiter, Marie Schmidt, and Michael Stiglmayr. The Line-Based Dial-a-Ride Problem. In 24th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2024). Open Access Series in Informatics (OASIcs), Volume 123, pp. 14:1-14:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@InProceedings{reiter_et_al:OASIcs.ATMOS.2024.14,
  author =	{Reiter, Kendra and Schmidt, Marie and Stiglmayr, Michael},
  title =	{{The Line-Based Dial-a-Ride Problem}},
  booktitle =	{24th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2024)},
  pages =	{14:1--14:20},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-350-8},
  ISSN =	{2190-6807},
  year =	{2024},
  volume =	{123},
  editor =	{Bouman, Paul C. and Kontogiannis, Spyros C.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2024.14},
  URN =		{urn:nbn:de:0030-drops-212024},
  doi =		{10.4230/OASIcs.ATMOS.2024.14},
  annote =	{Keywords: DARP, ridepooling, liDARP, public transport, on-demand}
}
Document
Multiobjective Optimization on a Budget (Dagstuhl Seminar 23361)

Authors: Richard Allmendinger, Carlos M. Fonseca, Serpil Sayin, Margaret M. Wiecek, and Michael Stiglmayr

Published in: Dagstuhl Reports, Volume 13, Issue 9 (2024)


Abstract
The Dagstuhl Seminar 23361 Multiobjective Optimization on a Budget carried on a series of seven previous Dagstuhl Seminars (04461, 06501, 09041, 12041, 15031, 18031, 20031) focused on Multiobjective Optimization. The original goal of this series has been to strengthen the links between the Evolutionary Multiobjective Optimization (EMO) and the Multiple Criteria Decision Making (MCDM) communities, two of the largest communities concerned with multiobjective optimization today. This seminar particularly focused on the case where the approaches from both communities may be challenged by limited resources. This report documents the program and the outcomes of Dagstuhl Seminar 23361 "Multiobjective Optimization on a Budget". Three major types of resource limitations were highlighted during the seminar: methodological, technical and human related. The effect of these limitations on optimization and decision-making quality, as well as methods to quantify and mitigate this influence, were considered in different working groups.

Cite as

Richard Allmendinger, Carlos M. Fonseca, Serpil Sayin, Margaret M. Wiecek, and Michael Stiglmayr. Multiobjective Optimization on a Budget (Dagstuhl Seminar 23361). In Dagstuhl Reports, Volume 13, Issue 9, pp. 1-68, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@Article{allmendinger_et_al:DagRep.13.9.1,
  author =	{Allmendinger, Richard and Fonseca, Carlos M. and Sayin, Serpil and Wiecek, Margaret M. and Stiglmayr, Michael},
  title =	{{Multiobjective Optimization on a Budget (Dagstuhl Seminar 23361)}},
  pages =	{1--68},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2024},
  volume =	{13},
  number =	{9},
  editor =	{Allmendinger, Richard and Fonseca, Carlos M. and Sayin, Serpil and Wiecek, Margaret M. and Stiglmayr, Michael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.9.1},
  URN =		{urn:nbn:de:0030-drops-198207},
  doi =		{10.4230/DagRep.13.9.1},
  annote =	{Keywords: evolutionary algorithms, expensive optimization, few-shot learning, machine learning, optimization, simulation}
}
Document
Solving the Dynamic Dial-a-Ride Problem Using a Rolling-Horizon Event-Based Graph

Authors: Daniela Gaul, Kathrin Klamroth, and Michael Stiglmayr

Published in: OASIcs, Volume 96, 21st Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2021)


Abstract
In many ridepooling applications transportation requests arrive throughout the day and have to be answered and integrated into the existing (and operated) vehicle routing. To solve this dynamic dial-a-ride problem we present a rolling-horizon algorithm that dynamically updates the current solution by solving an MILP formulation. The MILP model is based on an event-based graph with nodes representing pick-up and drop-off events associated with feasible user allocations in the vehicles. The proposed solution approach is validated on a set of real-word instances with more than 500 requests. In 99.5% of all iterations the rolling-horizon algorithm returned optimal insertion positions w.r.t. the current schedule in a time-limit of 30 seconds. On average, incoming requests are answered within 2.8 seconds.

Cite as

Daniela Gaul, Kathrin Klamroth, and Michael Stiglmayr. Solving the Dynamic Dial-a-Ride Problem Using a Rolling-Horizon Event-Based Graph. In 21st Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2021). Open Access Series in Informatics (OASIcs), Volume 96, pp. 8:1-8:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{gaul_et_al:OASIcs.ATMOS.2021.8,
  author =	{Gaul, Daniela and Klamroth, Kathrin and Stiglmayr, Michael},
  title =	{{Solving the Dynamic Dial-a-Ride Problem Using a Rolling-Horizon Event-Based Graph}},
  booktitle =	{21st Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2021)},
  pages =	{8:1--8:16},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-213-6},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{96},
  editor =	{M\"{u}ller-Hannemann, Matthias and Perea, Federico},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2021.8},
  URN =		{urn:nbn:de:0030-drops-148776},
  doi =		{10.4230/OASIcs.ATMOS.2021.8},
  annote =	{Keywords: Dial-a-Ride Problem, Ridepooling, Event-Based MILP, Rolling-Horizon, Dynamic Requests}
}
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