Multiobjective multiproduct batch plant design under uncertainty: Application to protein production

The design of batch plants necessary involves how equipment may be utilized, which means that plant scheduling and production must form an integral part of the design problem. The market demand for such products is usually changeable, and at the stage of conceptual design of a batch plant, it is almost impossible to obtain the precise information on the future product demand over the lifetime of the plant. This paper addresses the problem of the optimal design of batch plants with imprecise demands and proposes an alternative treatment of the imprecision by using concepts of fuzzy logic. For this purpose, we extended a Multi-Objective Genetic Algorithm (MOGA) developed in previous works, taking into account simultaneously three criteria, i.e. minimization of the investment cost, the operation cost and the total production time. The case of study is a multiproduct batch plant for the production of proteins taken from the literature. The methodology provides a set of scenarios that are helpful to the decision’s maker and constitutes a very promising framework for taken imprecision into account in new product development stage