The Convex Hull of Two Core Capacitated Network Design Problems

The network loading problem (NLP) is a specialized capacitated network design problem in which prescribed point-to-point demand between various pairs of nodes of a network must be met by installing (loading) a capacitated facility. We can load any number of units of the facility on each of the arcs...

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Main Authors: Magnanti, Thomas L., Mirchandani, Prakash, Vachani, Rita
Format: Working Paper
Language:en_US
Published: Massachusetts Institute of Technology, Operations Research Center 2004
Subjects:
Online Access:http://hdl.handle.net/1721.1/5164
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author Magnanti, Thomas L.
Mirchandani, Prakash
Vachani, Rita
author_facet Magnanti, Thomas L.
Mirchandani, Prakash
Vachani, Rita
author_sort Magnanti, Thomas L.
collection MIT
description The network loading problem (NLP) is a specialized capacitated network design problem in which prescribed point-to-point demand between various pairs of nodes of a network must be met by installing (loading) a capacitated facility. We can load any number of units of the facility on each of the arcs at a specified arc dependent cost. The problem is to determine the number of facilities to be loaded on the arcs that will satisfy the given demand at minimum cost. This paper studies two core subproblems of the NLP. The first problem, motivated by a Lagrangian relaxation approach for solving the problem, considers a multiple commodity, single arc capacitated network design problem. The second problem is a three node network; this specialized network arises in larger networks if we aggregate nodes. In both cases, we develop families of facets and completely characterize the convex hull of feasible solutions to the integer programming formulation of the problems. These results in turn strengthen the formulation of the NLP.
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spelling mit-1721.1/51642019-04-10T15:18:07Z The Convex Hull of Two Core Capacitated Network Design Problems Magnanti, Thomas L. Mirchandani, Prakash Vachani, Rita Convex hull, Facets, Network design, Capacitated facilities. The network loading problem (NLP) is a specialized capacitated network design problem in which prescribed point-to-point demand between various pairs of nodes of a network must be met by installing (loading) a capacitated facility. We can load any number of units of the facility on each of the arcs at a specified arc dependent cost. The problem is to determine the number of facilities to be loaded on the arcs that will satisfy the given demand at minimum cost. This paper studies two core subproblems of the NLP. The first problem, motivated by a Lagrangian relaxation approach for solving the problem, considers a multiple commodity, single arc capacitated network design problem. The second problem is a three node network; this specialized network arises in larger networks if we aggregate nodes. In both cases, we develop families of facets and completely characterize the convex hull of feasible solutions to the integer programming formulation of the problems. These results in turn strengthen the formulation of the NLP. 2004-05-28T19:26:00Z 2004-05-28T19:26:00Z 1990-06 Working Paper http://hdl.handle.net/1721.1/5164 en_US Operations Research Center Working Paper;OR 217-90 1716245 bytes application/pdf application/pdf Massachusetts Institute of Technology, Operations Research Center
spellingShingle Convex hull, Facets, Network design, Capacitated facilities.
Magnanti, Thomas L.
Mirchandani, Prakash
Vachani, Rita
The Convex Hull of Two Core Capacitated Network Design Problems
title The Convex Hull of Two Core Capacitated Network Design Problems
title_full The Convex Hull of Two Core Capacitated Network Design Problems
title_fullStr The Convex Hull of Two Core Capacitated Network Design Problems
title_full_unstemmed The Convex Hull of Two Core Capacitated Network Design Problems
title_short The Convex Hull of Two Core Capacitated Network Design Problems
title_sort convex hull of two core capacitated network design problems
topic Convex hull, Facets, Network design, Capacitated facilities.
url http://hdl.handle.net/1721.1/5164
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