A fuzzy multiobjective algorithm for multiproduct batch plant: Application to protein production

This paper addresses the problem of the optimal design of batch plants with imprecise demands and proposes an alternative treatment of the mprecision by using fuzzy concepts. For this purpose, we extended a multiobjective genetic algorithm (MOGA) developed in previous works, taking nto account simultaneously maximization of the net present value (NPV) and two other performance criteria, i.e. the production delay/advance nd a flexibility criterion. The former is computed by comparing the fuzzy computed production time to a given fuzzy production time horizon and he latter is based on the additional fuzzy demand that the plant is able to produce. The methodology provides a set of scenarios that are helpful to he decision’s maker and constitutes a very promising framework for taken imprecision into account in new product development stage.