2 Search Results for "Golestanian, Arnoosh"

Document
DOI: 10.4230/LIPIcs.CP.2023.17
Optimization Models for Pickup-And-Delivery Problems with Reconfigurable Capacities

Authors: Arnoosh Golestanian, Giovanni Lo Bianco, Chengyu Tao, and J. Christopher Beck

Published in: LIPIcs, Volume 280, 29th International Conference on Principles and Practice of Constraint Programming (CP 2023)

Abstract
When a transportation service accommodates both people and goods, operators sometimes opt for vehicles that can be dynamically reconfigured for different demands. Motivated by air service in remote communities in Canada’s north, we define a pickup-and-delivery problem in which aircraft can add or remove seats during a multi-stop trip to accommodate varying demands. Given the demand for people and cargo as well as a seat inventory at each location, the problem consists in finding a tour that picks up and delivers all demand while potentially reconfiguring the vehicle capacity at each location by adding or removing seats. We develop a total of six models using three different approaches: constraint programming, mixed integer programming, and domain-independent dynamic programming. Our numerical experiments indicate that domain-independent dynamic programming is able to substantially outperform the other technologies on both solution quality and run-time on a set of randomly generated instances spanning the size of real problems in northern Canada.
Cite as

Arnoosh Golestanian, Giovanni Lo Bianco, Chengyu Tao, and J. Christopher Beck. Optimization Models for Pickup-And-Delivery Problems with Reconfigurable Capacities. In 29th International Conference on Principles and Practice of Constraint Programming (CP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 280, pp. 17:1-17:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{golestanian_et_al:LIPIcs.CP.2023.17,
  author =	{Golestanian, Arnoosh and Bianco, Giovanni Lo and Tao, Chengyu and Beck, J. Christopher},
  title =	{{Optimization Models for Pickup-And-Delivery Problems with Reconfigurable Capacities}},
  booktitle =	{29th International Conference on Principles and Practice of Constraint Programming (CP 2023)},
  pages =	{17:1--17:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-300-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{280},
  editor =	{Yap, Roland H. C.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2023.17},
  URN =		{urn:nbn:de:0030-drops-190542},
  doi =		{10.4230/LIPIcs.CP.2023.17},
  annote =	{Keywords: Pickup and delivery, Dial-a-ride problem, Optimization}
}
Document
DOI: 10.4230/LIPIcs.APPROX-RANDOM.2017.5
Scheduling Problems over Network of Machines

Authors: Zachary Friggstad, Arnoosh Golestanian, Kamyar Khodamoradi, Christopher Martin, Mirmahdi Rahgoshay, Mohsen Rezapour, Mohammad R. Salavatipour, and Yifeng Zhang

Published in: LIPIcs, Volume 81, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2017)

Abstract
We consider scheduling problems in which jobs need to be processed through a (shared) network of machines. The network is given in the form of a graph the edges of which represent the machines. We are also given a set of jobs, each specified by its processing time and a path in the graph. Every job needs to be processed in the order of edges specified by its path. We assume that jobs can wait between machines and preemption is not allowed; that is, once a job is started being processed on a machine, it must be completed without interruption. Every machine can only process one job at a time. The makespan of a schedule is the earliest time by which all the jobs have finished processing. The flow time (a.k.a. the completion time) of a job in a schedule is the difference in time between when it finishes processing on its last machine and when the it begins processing on its first machine. The total flow time (or the sum of completion times) is the sum of flow times (or completion times) of all jobs. Our focus is on finding schedules with the minimum sum of completion times or minimum makespan. In this paper, we develop several algorithms (both approximate and exact) for the problem both on general graphs and when the underlying graph of machines is a tree. Even in the very special case when the underlying network is a simple star, the problem is very interesting as it models a biprocessor scheduling with applications to data migration.
Cite as

Zachary Friggstad, Arnoosh Golestanian, Kamyar Khodamoradi, Christopher Martin, Mirmahdi Rahgoshay, Mohsen Rezapour, Mohammad R. Salavatipour, and Yifeng Zhang. Scheduling Problems over Network of Machines. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 81, pp. 5:1-5:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

Copy BibTex To Clipboard

@InProceedings{friggstad_et_al:LIPIcs.APPROX-RANDOM.2017.5,
  author =	{Friggstad, Zachary and Golestanian, Arnoosh and Khodamoradi, Kamyar and Martin, Christopher and Rahgoshay, Mirmahdi and Rezapour, Mohsen and Salavatipour, Mohammad R. and Zhang, Yifeng},
  title =	{{Scheduling Problems over Network of Machines}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2017)},
  pages =	{5:1--5:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-044-6},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{81},
  editor =	{Jansen, Klaus and Rolim, Jos\'{e} D. P. and Williamson, David P. and Vempala, Santosh S.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX-RANDOM.2017.5},
  URN =		{urn:nbn:de:0030-drops-75547},
  doi =		{10.4230/LIPIcs.APPROX-RANDOM.2017.5},
  annote =	{Keywords: approximation algorithms, job-shop scheduling, min-sum edge coloring, minimum latency}
}
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