This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Column generation approaches to ship scheduling with flexible cargo sizes

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Brønmo, Geir () (Section of Managerial Economics and Operations Research)
Nygreen, Bjørn () (Section of Managerial Economics and Operations Research)
Lysgaard, Jens () (Department of Accounting, Aarhus School of Business)
Abstract

We present a Dantzig-Wolfe procedure for the ship scheduling problem with flexible cargo sizes. This problem is similar to the well-known pickup and delivery problem with time windows, but the cargo sizes are defined by an interval instead of a fixed value. We show that the introduction of flexible cargo sizes to the column generation framework is not straightforward, and we handle the flexible cargo sizes heuristically when solving the subproblems. This leads to convergence issues in the branch-and-price search tree, and the optimal solution cannot be guaranteed. Hence we have introduced a method that generates an upper bound on the optimal objective. We have compared our method with an a priori column generation approach, and our computational experiments on real world cases show that the Dantzig-Wolfe approach is faster than the a priori generation of columns, and we are able to deal with larger or more loosely constrained instances. By using the techniques introduced in this paper, a more extensive set of real world cases can be solved either to optimality or within a small deviation from optimality

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.hha.dk/bs/wp/log/L_2006_07.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by University of Aarhus, Aarhus School of Business, Department of Business Studies in its series CORAL Working Papers with number L-2006-07.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 28 pages
Date of creation: 01 Jun 2006
Date of revision:
Handle: RePEc:hhb:aarbls:2006-007

Contact details of provider:
Postal: The Aarhus School of Business, Fuglesangs Allé 4, DK-8210 Aarhus V, Denmark
Fax: + 45 86 15 19 43
Web page: http://www.asb.dk/about/departments/bs.aspx
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (Helle Vinbaek Stenholt).

Related research
Keywords: Transportation; integer programming; dynamic programming;

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  1. Dumas, Yvan & Desrosiers, Jacques & Soumis, Francois, 1991. "The pickup and delivery problem with time windows," European Journal of Operational Research, Elsevier, vol. 54(1), pages 7-22, September. [Downloadable!] (restricted)
  2. Persson, Jan A. & Gothe-Lundgren, Maud, 2005. "Shipment planning at oil refineries using column generation and valid inequalities," European Journal of Operational Research, Elsevier, vol. 163(3), pages 631-652, June. [Downloadable!] (restricted)
Full references

Statistics
Access and download statistics

Did you know? You may want to explore EconPapers, which displays the same data as IDEAS in a different way.

This page was last updated on 2009-12-24.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.