Design of Multiproduct Batch Plants with Uncertain Demands

The problem of how t,o design mukiproduct batch plant,s for the case of uncertain product demands described by any continuous/discrete probability distributional form, is considered in this paper. Based on a stochastic programming formulation, featuring an objective function comprising investment costs for equipment sizing, expected revenues from product sales and a pena.lty term accounting for partial feasibility and unfilled orders, it is first shown that the relaxation of the feasibility requirement enables the reformulation of the problem as a single, yet large-sca.le and nonconvex, nonlinear optimization model. The exploitation of the special structure of the multiproduct batch plant design model, however, results in orders of magnitude reduction of t,he number of relaxed dual problems which are required for the computationa.lly efficient applica.tion of the global opt,imiza.tion algoribhm (GOP) of Floudas and Visweswaran (1990).