edoc-Server der Humboldt-Universität zu Berlin

SPEPS Preprint

Author(s): Maria L.A.G. Cremers, University of Groningen
Willem K. Klein Haneveld, University of Groningen
Maarten H. van der Vlerk, University of Groningen
Title: A dynamic day-ahead paratransit planning problem
Date of Acceptance: 06.03.2008
Submission Date: 04.10.2007
Series Title: Stochastic Programming E-Print Series
(SPEPS)
Editors: Julie L. Higle; Werner Römisch; Surrajeet Sen
Complete Preprint: pdf (urn:nbn:de:kobv:11-10086937)
Keywords (eng): stochastic programming, paratransit transport, online optimization
Metadata export: To export the complete metadata set as Endote or Bibtex format please click to the appropriate link. Endnote   Bibtex  
print on demand: If you click on this icon you can order a print copy of this publication. Bestellung als gedruckte und gebundene Version bei epubli.de, Ausführung der Bestellung erst nach Bestätigung auf den epubli.de-Seiten

Abstract (eng):
We consider a dynamic planning problem for the transport of elderly and disabled people. The focus is on a decision to make one day ahead: which requests to serve with own vehicles, and which ones to assign to subcontractors, under uncertainty of late requests which are gradually revealed during the day of operation. We call this problem the Dynamic Day-ahead Paratransit Planning problem. The developed model is a non- standard two-stage recourse model in which ideas from stochastic programming and online optimization are combined: in the first stage clustered requests are assigned to vehicles, and in the dynamic second-stage problem an event-driven approach is used to cluster the late requests once they are revealed and subsequently assign them to vehicles. A genetic algorithm is used to solve the model. Computational results are presented for randomly generated data sets. Furthermore, a comparison is made to a similar problem we studied earlier in which the simplifying but unrealistic assumption has been made that all late requests are revealed at the beginning of the day of operation.
Access Statistics: These data concerning access statistics for individual documents have been compiled using the webserver log files aggregated by AWSTATS. They refer to a monthly access count to the full text documents as well as to the entry page.
 
As for format versions of a document which consist of multiple files (such as HTML) the highest monthly access number to one of the files (chapters) is shown respectivly.
 
To see the detailled access numbers please move the mouse pointer over the single bars of the digaram.
Startseite: 5 Zugriffe PDF: 20 Zugriffe Startseite: 2 Zugriffe PDF: 26 Zugriffe Startseite: 1 Zugriffe PDF: 41 Zugriffe Startseite: 3 Zugriffe PDF: 19 Zugriffe Startseite: 1 Zugriffe PDF: 20 Zugriffe Startseite: 1 Zugriffe PDF: 27 Zugriffe Startseite: 4 Zugriffe PDF: 32 Zugriffe PDF: 28 Zugriffe Startseite: 3 Zugriffe PDF: 22 Zugriffe Startseite: 1 Zugriffe PDF: 7 Zugriffe Startseite: 1 Zugriffe PDF: 18 Zugriffe Startseite: 1 Zugriffe PDF: 17 Zugriffe Startseite: 3 Zugriffe PDF: 15 Zugriffe Startseite: 4 Zugriffe PDF: 6 Zugriffe Startseite: 3 Zugriffe PDF: 15 Zugriffe PDF: 8 Zugriffe Startseite: 4 Zugriffe PDF: 12 Zugriffe
Jan
16
Feb
16
Mar
16
Apr
16
May
16
Jun
16
Jul
16
Aug
16
Sep
16
Oct
16
Nov
16
Dec
16
Jan
17
Feb
17
Mar
17
Apr
17
May
17
Monat Jan
16
Feb
16
Mar
16
Apr
16
May
16
Jun
16
Jul
16
Aug
16
Sep
16
Oct
16
Nov
16
Dec
16
Jan
17
Feb
17
Mar
17
Apr
17
May
17
Startseite 5 2 1 3 1 1 4   3 1 1 1 3 4 3   4
PDF 20 26 41 19 20 27 32 28 22 7 18 17 15 6 15 8 12

Gesamtzahl der Zugriffe seit Jan 2016:

  • Startseite – 37 (2.18 pro Monat)
  • PDF – 333 (19.59 pro Monat)
 
 
Generated at 24.06.2017, 01:58:57