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A PREEMPTIVE VALUE‐FUNCTION METHOD APPROACH FOR MULTIOBJECTIVE LINEAR PROGRAMMING PROBLEMS
Author(s) -
Ringuest Jeffrey L.,
Gulledge Thomas R.
Publication year - 1983
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1983.tb00170.x
Subject(s) - mathematical optimization , bellman equation , computer science , function (biology) , value (mathematics) , linear programming , goal programming , quadratic programming , mathematics , machine learning , evolutionary biology , biology
Many common decision‐making situations require integration of a number of objectives or goals into a single objective function to be optimized. A number of techniques for performing this analysis are presented in the literature. These procedures generally require a tradeoff between realism and tractability. The present approach uses the idea of preemptive priority levels with an approximate value function at each level. An efficient experimental design is used to assess directly a quadratic approximation of the multiattribute value functions. An existing algorithm is then used to solve the resulting problem. This procedure is shown to give good results when compared to both the value‐function method and goal programming.