An SDP approach for multiperiod mixed 0-1 linear programming models with stochastic dominance constraints for risk management

摘要: In this paper we consider multiperiod mixed 0-1 linear programming models under uncertainty. We propose a risk averse strategy using stochastic dominance constraints (SDC) induced by mixed-integer recourse as the measure. The SDC extends existing literature to multistage case and includes both first-order second-order constraints. dynamic (SDP) solution approach, where one has overcome negative impact of cross-scenario on decomposability model. our computational experience compare SDP approach against commercial optimization package, in terms accuracy elapsed time. use supply chain planning instances, procurement, production, inventory, distribution decisions need be made demand confirm hardness testbed, benchmark cannot find feasible for half test instances while always one, show appealing tradeoff SDP, time, when solving medium-to-large instances.