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Analyzing Multi-Objective Linear and Mixed Integer Programs by Lagrange Multipliers

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dc.contributor.author Ramakrishnan, V. S. en_US
dc.contributor.author Shapiro, Jeremy F., 1939- en_US
dc.date.accessioned 2004-05-28T19:33:39Z
dc.date.available 2004-05-28T19:33:39Z
dc.date.issued 1991-08 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/5322
dc.description.abstract A new method for multi-objective optimization of linear and mixed programs based on Lagrange multiplier methods is developed. The method resembles, but is distinct from, objective function weighting and goal programming methods. A subgradient optimization algorithm for selecting the multipliers is presented and analyzed. The method is illustrated by its application to a model for determining the weekly re-distribution of railroad cars from excess supply areas to excess demand areas, and to a model for balancing cost minimization against order completion requirements for a dynamic lot size model. en_US
dc.format.extent 1442328 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US en_US
dc.publisher Massachusetts Institute of Technology, Operations Research Center en_US
dc.relation.ispartofseries Operations Research Center Working Paper;OR 258-91 en_US
dc.subject Programming: linear and integer, multiple criteria, relaxation/subgradient. en_US
dc.title Analyzing Multi-Objective Linear and Mixed Integer Programs by Lagrange Multipliers en_US
dc.type Working Paper en_US


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