Models and Methods for Merge-In-Transit Operations

We develop integer programming formulations and solution methods for addressing operational issues in merge-in-transit distribution systems. The models account for various complex problem features including the integration of inventory and transportation decisions, the dynamic and multimodal compone...

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Main Authors: Croxton, Keely L., Gendon, Bernard, Magnanti, Thomas L.
Format: Working Paper
Language:en_US
Published: Massachusetts Institute of Technology, Operations Research Center 2004
Online Access:http://hdl.handle.net/1721.1/5135
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author Croxton, Keely L.
Gendon, Bernard
Magnanti, Thomas L.
author_facet Croxton, Keely L.
Gendon, Bernard
Magnanti, Thomas L.
author_sort Croxton, Keely L.
collection MIT
description We develop integer programming formulations and solution methods for addressing operational issues in merge-in-transit distribution systems. The models account for various complex problem features including the integration of inventory and transportation decisions, the dynamic and multimodal components of the application, and the non-convex piecewise linear structure of the cost functions. To accurately model the cost functions, we introduce disaggregation techniques that allow us to derive a hierarchy of linear programming relaxations. To solve these relaxations, we propose a cutting-plane procedure that combines constraint and variable generation with rounding and branch-and-bound heuristics. We demonstrate the effectiveness of this approach on a large set of test problems with instances with up to almost 500,000 integer variables derived from actual data from the computer industry. Key words : Merge-in-transit distribution systems, logistics, transportation, integer programming, disaggregation, cutting-plane method.
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spelling mit-1721.1/51352019-04-09T16:03:14Z Models and Methods for Merge-In-Transit Operations Croxton, Keely L. Gendon, Bernard Magnanti, Thomas L. We develop integer programming formulations and solution methods for addressing operational issues in merge-in-transit distribution systems. The models account for various complex problem features including the integration of inventory and transportation decisions, the dynamic and multimodal components of the application, and the non-convex piecewise linear structure of the cost functions. To accurately model the cost functions, we introduce disaggregation techniques that allow us to derive a hierarchy of linear programming relaxations. To solve these relaxations, we propose a cutting-plane procedure that combines constraint and variable generation with rounding and branch-and-bound heuristics. We demonstrate the effectiveness of this approach on a large set of test problems with instances with up to almost 500,000 integer variables derived from actual data from the computer industry. Key words : Merge-in-transit distribution systems, logistics, transportation, integer programming, disaggregation, cutting-plane method. 2004-05-28T19:24:44Z 2004-05-28T19:24:44Z 2001-09 Working Paper http://hdl.handle.net/1721.1/5135 en_US Operations Research Center Working Paper;OR 351-01 1744 bytes 3046528 bytes application/pdf application/pdf Massachusetts Institute of Technology, Operations Research Center
spellingShingle Croxton, Keely L.
Gendon, Bernard
Magnanti, Thomas L.
Models and Methods for Merge-In-Transit Operations
title Models and Methods for Merge-In-Transit Operations
title_full Models and Methods for Merge-In-Transit Operations
title_fullStr Models and Methods for Merge-In-Transit Operations
title_full_unstemmed Models and Methods for Merge-In-Transit Operations
title_short Models and Methods for Merge-In-Transit Operations
title_sort models and methods for merge in transit operations
url http://hdl.handle.net/1721.1/5135
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