Design and retrofit of multiobjective batch plants via a multicriteria genetic algorithm

This paper addresses the development of a two-stage methodology for multiobjective batch plant design and retrofit, according to multiple criteria. At the upper level (master problem), a multiobjective genetic algorithm (MOGA) is implemented for managing the problem of design or retrofit and proposes several plant structures. At the inner level (slave problem), a discrete event simulator (DES) evaluates the technical feasibility of the proposed configurations. The basic principles of the DES are first recalled; then the following section develops a MOGA based on the combination of a single objective genetic algorithm (SOGA) and a Pareto sort (PS) procedure. Finally, a didactic example, related to the manufacturing of four products by using three types of equipment of discrete sizes. illustrates the approach. First, two criteria (investment cost and number of different sizes for units of the plant) are considered for designing the workshop. Then starting from the best solution with regard to investment cost found in the design phase, the plant is retrofitted for manufacturing a double production. Finally, assuming a double production at the design phase, the workshop is designed again. In terms on investment cost, this new solution yields a significant saving compared with the retrofitted plant. In fact, redesigning a new plant, may challenge the retrofitting choice. Secondly, an additional criterion concerning the number of production campaigns for reaching the steady-state or oscillatory regime is introduced, and the same approach (designing, retrofitting and redesigning) is carried out, leading to the same conclusion as in the bicriteria case. (C) 2003 Elsevier Ltd. All rights reserved.