2 Search Results for "Perea, Andres"

Document
DOI: 10.4230/OASIcs.ATMOS.2021.4
Solving the Home Service Assignment, Routing, and Appointment Scheduling (H-SARA) Problem with Uncertainties

Authors: Syu-Ning Johnn, Yiran Zhu, Andrés Miniguano-Trujillo, and Akshay Gupte

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

Abstract
The Home Service Assignment, Routing, and Appointment scheduling (H-SARA) problem integrates the strategic fleet-sizing, tactical assignment, operational vehicle routing and scheduling problems at different decision levels, with a single period planning horizon and uncertainty (stochasticity) from the service duration, travel time, and customer cancellation rate. We propose a stochastic mixed-integer linear programming model for the H-SARA problem. Additionally, a reduced deterministic version is introduced which allows to solve small-scale instances to optimality with two acceleration approaches. For larger instances, we develop a tailored two-stage decision support system that provides high-quality and in-time solutions based on information revealed at different stages. Our solution method aims to reduce various costs under stochasticity, to create reasonable routes with balanced workload and team-based customer service zones, and to increase customer satisfaction by introducing a two-stage appointment notification system updated at different time stages before the actual service. Our two-stage heuristic is competitive to CPLEX’s exact solution methods in providing time and cost-effective decisions and can update previously-made decisions based on an increased level of information. Results show that our two-stage heuristic is able to tackle reasonable-size instances and provides good-quality solutions using less time compared to the deterministic and stochastic models on the same set of simulated instances.
Cite as

Syu-Ning Johnn, Yiran Zhu, Andrés Miniguano-Trujillo, and Akshay Gupte. Solving the Home Service Assignment, Routing, and Appointment Scheduling (H-SARA) Problem with Uncertainties. In 21st Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2021). Open Access Series in Informatics (OASIcs), Volume 96, pp. 4:1-4:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{johnn_et_al:OASIcs.ATMOS.2021.4,
  author =	{Johnn, Syu-Ning and Zhu, Yiran and Miniguano-Trujillo, Andr\'{e}s and Gupte, Akshay},
  title =	{{Solving the Home Service Assignment, Routing, and Appointment Scheduling (H-SARA) Problem with Uncertainties}},
  booktitle =	{21st Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2021)},
  pages =	{4:1--4:21},
  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-dev.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2021.4},
  URN =		{urn:nbn:de:0030-drops-148737},
  doi =		{10.4230/OASIcs.ATMOS.2021.4},
  annote =	{Keywords: Home Health Care, Mixed-Integer Linear Programming, Two-stage Stochastic, Uncertainties A Priori Optimisation, Adaptive Large Neighbourhood Search, Monte-Carlo Simulation}
}
Document
DOI: 10.4230/DagSemProc.05011.4
A Network Approach to Bayes-Nash Incentive Compatible Mechanisms

Authors: Rudolf Müller, Andres Perea, and Sascha Wolf

Published in: Dagstuhl Seminar Proceedings, Volume 5011, Computing and Markets (2005)

Abstract
This paper provides a characterization of Bayes-Nash incentive compatible mechanisms in settings where agents have one-dimensional or multi-dimensional types, quasi-linear utility functions and interdependent valuations. The characterization is derived in terms of conditions for the underlying allocation function. We do this by making a link to network theory and building complete directed graphs for agents type spaces. We show that an allocation rule is Bayes-Nash incentive compatible if and only if these graphs have no negative, finite cycles. In the case of one-dimensional types and given certain properties for agents valuation functions, we show that this condition reduces to the absence of negative 2-cycles. In the case of multi-dimensional types and given a linearity requirement on the valuation functions, we show that this condition reduces to the absence of negative 2-cycles and an integratebility condition on the valuation functions.
Cite as

Rudolf Müller, Andres Perea, and Sascha Wolf. A Network Approach to Bayes-Nash Incentive Compatible Mechanisms. In Computing and Markets. Dagstuhl Seminar Proceedings, Volume 5011, pp. 1-10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)

Copy BibTex To Clipboard

@InProceedings{muller_et_al:DagSemProc.05011.4,
  author =	{M\"{u}ller, Rudolf and Perea, Andres and Wolf, Sascha},
  title =	{{A Network Approach to Bayes-Nash Incentive Compatible Mechanisms}},
  booktitle =	{Computing and Markets},
  pages =	{1--10},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2005},
  volume =	{5011},
  editor =	{Daniel Lehmann and Rudolf M\"{u}ller and Tuomas Sandholm},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.05011.4},
  URN =		{urn:nbn:de:0030-drops-2056},
  doi =		{10.4230/DagSemProc.05011.4},
  annote =	{Keywords: compact representation of games, congestion games, local-effect games, action-graph gamescomputational markets; auctions; bidding strategiesNegotiatio}
}
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