An Algorithm for a Class of Nonconvex Programming Problems with Nonlinear Fractional Objectives

Ravi Jagannathan

Management Science, 1985, vol. 31, issue 7, 847-851

Abstract: In public policy decision making and in capital planning fractional criterion functions occur. For a given set of desirable target values (goals) \tau i , this paper develops an algorithm for solving a nonconvex programming problem of the type: Min x\in s Max i {\phi i (f i (x)/g i (x) - \tau i ), i = 1, ..., m} where f i are convex functions, g i are concave functions over the convex subset S of R n and \phi i are nondecreasing gauge functions. Here \phi i (\cdot ) is the penalty incurred whenever the fractional objective f i /g i deviates from the target value \tau i , the problem is then to choose an x that minimizes the maximum penalty incurred.

Keywords: programming: nonlinear; algorithms (search for similar items in EconPapers)
Date: 1985
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