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http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/4007Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.creator | Bossert, J.M. | - |
| dc.creator | Magnanti, Thomas L. | - |
| dc.date | 2003-12-23T02:45:18Z | - |
| dc.date | 2003-12-23T02:45:18Z | - |
| dc.date | 2002-01 | - |
| dc.date.accessioned | 2013-10-09T02:33:41Z | - |
| dc.date.available | 2013-10-09T02:33:41Z | - |
| dc.date.issued | 2013-10-09 | - |
| dc.identifier | http://hdl.handle.net/1721.1/4007 | - |
| dc.identifier.uri | http://koha.mediu.edu.my:8181/xmlui/handle/1721 | - |
| dc.description | We model Pup Matching, the logistics problem of matching or pairing semitrailers known as pups to cabs able to tow one or two pups simultaneously, as an NP-complete version of the Network Loading Problem (NLP). We examine a branch and bound solution approach tailored to the NLP formulation through the use of three families of cutting planes and four heuristic procedures. Theoretically, we specify facet defining conditions for a cut family that we refer to as odd flow inequalities and show that each heuristic yields a 2-approximation. Computationally, the cheapest of the four heuristic values achieved an average error of 1.3% among solved test problems randomly generated from realistic data. The branch and bound method solved to optimality 67% of these problems. Application of the cutting plane families reduced the average relative difference between upper and lower bounds prior to branching from 18.8% to 6.4%. | - |
| dc.description | Singapore-MIT Alliance (SMA) | - |
| dc.format | 205898 bytes | - |
| dc.format | application/pdf | - |
| dc.language | en_US | - |
| dc.relation | High Performance Computation for Engineered Systems (HPCES); | - |
| dc.subject | network loading | - |
| dc.subject | network design | - |
| dc.subject | cutting planes | - |
| dc.title | Pup Matching: Model Formulations and Solution Approaches | - |
| dc.type | Article | - |
| Appears in Collections: | MIT Items | |
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