IMA Journal of Numerical Analysis · 1996 · 128 citations · 0 references
Natural SciencesComputer ScienceAlgorithmsDesign OptimizationOptimizationConstrained OptimizationConvex OptimizationGlobal OptimizationGradient-based OptimizationOptimization TheoryUnconstrained OptimizationConvergenceGlobal Convergence Analysis
This paper investigates the global convergence properties of the Fletcher-Reeves (FR) method for unconstrained optimization. In a simple way, we prove that a kind of inexact line search condition can ensure the convergence of the FR method. Several examples are constructed to show that, if the search conditions are relaxed, the FR method may produce an ascent search direction, which implies that our result cannot be improved.