DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kwon, O | ko |
dc.contributor.author | Kang, DH | ko |
dc.contributor.author | Lee, K | ko |
dc.contributor.author | Park, Sungsoo | ko |
dc.date.accessioned | 2008-10-08T13:37:17Z | - |
dc.date.available | 2008-10-08T13:37:17Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 1999-09 | - |
dc.identifier.citation | NAVAL RESEARCH LOGISTICS, v.46, no.6, pp.640 - 653 | - |
dc.identifier.issn | 0894-069X | - |
dc.identifier.uri | http://hdl.handle.net/10203/7583 | - |
dc.description.abstract | In this paper, we consider a new weapon-target allocation problem with the objective of minimizing the overall firing cost. The problem is formulated as a nonlinear integer programming model. We applied Lagrangian relaxation and a branch-and-bound method to the problem after transforming the nonlinear constraints into linear ones. An efficient primal heuristic is developed to find a feasible solution to the problem to facilitate the procedure. In the branch-and-bound method, three different branching rules are considered and the performances are evaluated. Computational results using randomly generated data are presented. (C) 1999 John Wiley & Sons, Inc. | - |
dc.language | English | - |
dc.language.iso | en_US | en |
dc.publisher | JOHN WILEY SONS INC | - |
dc.title | Lagrangian relaxation approach to the targeting problem | - |
dc.type | Article | - |
dc.identifier.wosid | 000082034400003 | - |
dc.identifier.scopusid | 2-s2.0-0033308910 | - |
dc.type.rims | ART | - |
dc.citation.volume | 46 | - |
dc.citation.issue | 6 | - |
dc.citation.beginningpage | 640 | - |
dc.citation.endingpage | 653 | - |
dc.citation.publicationname | NAVAL RESEARCH LOGISTICS | - |
dc.embargo.liftdate | 9999-12-31 | - |
dc.embargo.terms | 9999-12-31 | - |
dc.contributor.localauthor | Park, Sungsoo | - |
dc.contributor.nonIdAuthor | Kwon, O | - |
dc.contributor.nonIdAuthor | Kang, DH | - |
dc.contributor.nonIdAuthor | Lee, K | - |
dc.type.journalArticle | Article | - |
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