This paper addresses the problem of integrating in a single model operational optimization and cyclic scheduling of continuous plants. Considered are multiproduct, multistage plants with finite intermediate storage capacity (FIS). A combined optimization approach introduces synergic effects for more effective scheduling and plant operation (Alle and Pinto, 2001a,b). The representation proposed for this problem results in an MINLP model with a nonconvex feasible region and nonconvex objective function. In order to deal with nonconvexity, a spatial branch-and-bound global optimization algorithm is applied. Results show that the global approach is effectively able to yield more profitable solutions than those obtained by local optimization methods.

The problems of scheduling and optimization of operational conditions in multistage, multiproduct continuous plants with intermediate storage are simultaneously addressed. An MINLP model, called TSPFLOW, which is based on the TSP formulation for product sequencing, is proposed to schedule the operation of such plants. TSPFLOW yields a one-order-of-magnitude CPU time reduction as well as the solution of instances larger than those formerly reported (Pinto and Grossmann, 1994). Secondly, processing rates and yields are introduced as additional optimization variables in order to state the simultaneous problem of scheduling with operational optimization. Results show that trade-offs are very complex and that the development of a straightforward (rule of thumb) method to optimally schedule the operation is less effective than the proposed approach.