We propose a solution strategy for fractional programming problems of the form max x∈x g(x)/ φ(u(x)), where the functionφ satisfies certain convexity conditions. It is shown that subject to these conditions optima...
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We propose a solution strategy for fractional programming problems of the form maxclass="a-plus-plus"> x∈x g(x)/ φ(u(x)), where the functionφ satisfies certain convexity conditions. It is shown that subject to these conditions optimal solutions to this problem can be obtained from the solution of the problem maxclass="a-plus-plus"> x∈x g(x) + λu(x), whereλ is an exogenous parameter. The proposed strategy combines fractional programming andc-programming techniques. A maximal mean-standard deviation ratio problem is solved to illustrate the strategy in action.
作者：
SNIEDOVIcH, MCSIR
NATL RES INST MATH SCIPOB 395PRETORIA 0001SOUTH AFRICA
A new format is proposed for fractional programming problems. This format gives full expression to the fact that the parametric approach to fractional programming problems is rooted in a first-order necessary and suff...
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A new format is proposed for fractional programming problems. This format gives full expression to the fact that the parametric approach to fractional programming problems is rooted in a first-order necessary and sufficient optimality condition. It is thus shown that although traditionally it has not been construed as such, the parametric approach is in fact classical par excellence. [ABSTRAcT FROM AUTHOR]
Optimization problems requiring the minimization of pseudolinear functions and additive concave functions are examined from the standpoint of c-programming. A simple algorithm designed for pseudolinear problems is set...
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Optimization problems requiring the minimization of pseudolinear functions and additive concave functions are examined from the standpoint of c-programming. A simple algorithm designed for pseudolinear problems is set out, and an exlusionary rule for additive separable concave problems is formulated.
A solution procedure is proposed for a class of deterministic sequential decision problems whose objective functions are of the form Σf n(x n)+Φ(Σg n(x n)) where Φ is differentiable and either concave or convex. T...
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A solution procedure is proposed for a class of deterministic sequential decision problems whose objective functions are of the form Σf class="a-plus-plus">n(x class="a-plus-plus">n)+Φ(Σg class="a-plus-plus">n(x class="a-plus-plus">n)) where Φ is differentiable and either concave or convex. The procedure calls for the collaboration between dynamicprogramming and c-programming, and is demonstrated in our treatment of a minimum variance type problem.
This paper presents the essentials of a method designed to solve optimization problems whose objective functions are of the form g ( x )+ ψ ( u ( x )), where ψ is differentiable and either concave or convex. It is s...
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This paper presents the essentials of a method designed to solve optimization problems whose objective functions are of the form g ( x )+ ψ ( u ( x )), where ψ is differentiable and either concave or convex. It is shown that solutions to such problems can be obtained through the solutions of the Lagrangian problem whose objective function is of the form g ( x )+ λu ( x ).
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