A Simulated Annealing Approach for the BiObjective Design and Scheduling of Multipurpose Batch Plants

Like in most real-world problems, the design of multipurpose batch industrial facilities involves multiple objectives, which must be reconciled with a view to maximize profit. The use of this or other equivalent single criterion is the conventional way to evaluate the economic performance of an industrial plant. However, rather than employing one single criterion, plant revenues and costs can be handled separately, thus allowing the decision-maker to gain a better perception of the investment options. This latter approach, which is particularly relevant for a batch facility, is followed in this work, therefore leading to a multi-objective optimization and in turn to the definition of the efficient frontier which is defined as the locus of the optimal solutions so found. The nature and dimension of these problems usually lead to large mixed integer linear program (MILP) formulations that come associated with a high computational burden. In order to overcome this difficulty, a meta-heuristic approach, based on the Simulated Annealing (SA) methodology is developed and a sensitivity analysis performed on the main parameters. The proposed approached is compared with the exact approach, proposed by Pinto et al.(2008a).