Algorithms (solution methods) are used for optimal decision making with multiple objectives in operations research, management science, economics, finance and engineering design. An optimal decision needs to take into consideration possible future uncertainties which, as they become known, result in a necessary revision of the decision and the consideration of new future uncertainties. This volume is study of this topic. It is a distillation of research in developing methodologies and reflects research in this area. The question of multiple objective decision making with a nonlinear static problem framework is considered using quadratic programming, nonlinear programming, nonlinear constrained min-max, mean-variance optimization and noncooperative Nash games.