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

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.

Identiferoai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/5322
Date08 1900
CreatorsRamakrishnan, V. S., Shapiro, Jeremy F., 1939-
PublisherMassachusetts Institute of Technology, Operations Research Center
Source SetsM.I.T. Theses and Dissertation
Languageen_US
Detected LanguageEnglish
TypeWorking Paper
Format1442328 bytes, application/pdf
RelationOperations Research Center Working Paper;OR 258-91

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