A variant of projected gradient method for quasi-convex optimization problems with a competitive search strategy
L. R. Lucambio Perez | Bello Cruz, J. Y.
Quasi-convex optimization | Armijo search | Projected gradient method
We present the projected gradient method for solving constrained quasi-convex minimization problem with a competitive search strategy, i.e., an appropriate stepsize rule through an Armijo-search along feasible direction obtaining global convergence properties. Differently from other similar stepsize rule, we perform only one projection onto the feasible set per iteration, rather than one projection for each tentative step during the search of the stepsize, which represents a considerable saving when the projection is computationally expensive.