| Abstract: | A minimax solution to a stochastic program occurs when the objective function is maximized subject to the random parameters jointly taking on their most adverse or pessimistic values. Minimax solutions have been proposed for decision making in agricultural planning, and to provide a lower bound to the values of the objective function of the “wait and see” stochastic program. In this paper a non-convex minimax problem and the occurrence of local optima are discussed. A global algorithm is presented for the minimax problem of a stochastic program in which some of the right hand side parameters are stochastic. It is also shown how minimax solutions may be obtained where stochastic parameters occur solely in the objective function, and in the objective function and right hand sides simultaneously. |
