A method is proposed for the solution of minimax optimization problems in which the
individual functions involved are convex. The method consists of solving a problem with an objective
function which ia the sum of high powers or strong exponentials of the separate components of the
original objective function. The resulting objective function. which is equivalent at the limit to the
minimax one. is shown to be smooth as well as convex. Any efficient nonlinear programming method
can be utilized for solving the equivalent problem. A number of examples are discussed.