1. Department of Mathematics , Lewis and Clark College, Portland, Oregon, 97219, U.S.A.;2. Department of Mathematics , Michigan State University , East Lansing, Michigan, 48824, U.S.A.
Abstract:
This paper presents a feasible direction algorithm for the minimization of a pseudoconvex function over a smooth, compact, convex set. We establish that each cluster point of the generated sequence is an optimal solution of the problem without introducing anti-jamming procedures. Each iteration of the algorithm involves as subproblems only one line search for a zero of a continuously differentiable convex function and one univariate function minimization on a compact interval.