A technique is described for solving generalizedgeometric programs whose constraints include one or more strict equalities. The algorithm solves a sequence of penalized geometric programs; the penalty functions are d...
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A technique is described for solving generalizedgeometric programs whose constraints include one or more strict equalities. The algorithm solves a sequence of penalized geometric programs; the penalty functions are derived from the arithmetic-geometric inequality as condensed posynomials. Two examples serve to illustrate the idea.
作者：
JEFFERSON, TRSCOTT, CHLecturer
School of Mechanical and Industrial Engineering University of New South Wales Kensington New South Wales Australia
The interest in convexity in optimal control and the calculus of variations has gone through a revival in the past decade. In this paper, we extend the theory of generalized geometric programming to infinite dimension...
详细信息
The interest in convexity in optimal control and the calculus of variations has gone through a revival in the past decade. In this paper, we extend the theory of generalized geometric programming to infinite dimensions in order to derive a dual problem for the convex optimal control problem. This approach transfers explicit constraints in the primal problem to the dual objective functional.
Fenchel's duality theorem is extended to generalized geometric programming with explicit constraints—an extension that also generalizes and strengthens Slater's version of the Kuhn-Tucker theorem.
Fenchel's duality theorem is extended to generalized geometric programming with explicit constraints—an extension that also generalizes and strengthens Slater's version of the Kuhn-Tucker theorem.
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