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http://hdl.handle.net/11375/5450
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DC Field | Value | Language |
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dc.contributor.author | Dowling, Douglas Paul | en_US |
dc.contributor.author | Love, Robert F. | en_US |
dc.contributor.author | McMaster University, Faculty of Business | en_US |
dc.date.accessioned | 2014-06-17T20:38:56Z | - |
dc.date.available | 2014-06-17T20:38:56Z | - |
dc.date.created | 2013-12-23 | en_US |
dc.date.issued | 1984-03 | en_US |
dc.identifier.other | dsb/112 | en_US |
dc.identifier.other | 1111 | en_US |
dc.identifier.other | 4944135 | en_US |
dc.identifier.uri | http://hdl.handle.net/11375/5450 | - |
dc.description | <p>22, 7 p. ; Includes bibliographical references (p. 21-22). ; "March, 1984".</p> | en_US |
dc.description.abstract | <p>Single and multi-facility location problems are often solved with iterative computational procedures. Although these procedures have been proven to converge, in practice it is desirable to be able to compute a· lower bound on the objective function at each iteration. This enables the user to stop the iterative process when the objective function is within a pre-specified tolerance of the optimum value. In this paper· we generalize a new bounding method to include multi-facility problems with eP distances. A proof is given that for Euclidean distance problems the new bounding procedure is superior to two other known methods. Numerical results are given for the three methods.</p> | en_US |
dc.relation.ispartofseries | Research and working paper series (McMaster University, Faculty of Business) | en_US |
dc.relation.ispartofseries | no. 219 | en_US |
dc.subject.lcc | Industrial location > Data processing Industrial location > Planning > Data processing Mathematical optimization | en_US |
dc.title | Bounding methods for facilities location algorithms | en_US |
dc.type | article | en_US |
Appears in Collections: | DeGroote School of Business Working Paper Series |
Files in This Item:
File | Size | Format | |
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fulltext.pdf | 1.04 MB | Adobe PDF | View/Open |
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