A simplified test for optimality |
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Authors: | R. Abrams L. Kerzner |
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Affiliation: | (1) Graduate School of Business, University of Chicago, Chicago, Illinois;(2) Department of National Defense, Ottawa, Canada |
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Abstract: | A simplification of recent characterizations of optimality in convex programming involving the cones of decrease and constancy of the objective and constraint functions is presented. In the original characterization due to Ben-Israelet al., optimality was verified or a feasible direction of decrease was determined by considering a number of sets equal to the number of subsets of the set of binding constraints. By first finding the set of constraints which is binding at every feasible point, it is possible to verify optimality or determine a feasible direction of decrease by considering a single set. In the case of faithfully convex functions, this set can be found by solving at mostp systems of linear equations and inequalities, wherep is the number of constraints.This work was partly supported by NSF Grant No. Eng 76-10260. |
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Keywords: | Optimality convex programming feasible directions cones of decrease cones of constancy |
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