A disjunctive programming model and a rolling horizon algorithm for optimal multiperiod capacity expansion in a multiproduct batch plant

This paper addresses a multiperiod mixed integer nonlinear programming problem for the capacity expansion of multiproduct batch plants. Given a certain batch plant with its current configuration, product recipes, and growing production targets, modular expansions are wanted so that new demand can be met. Unlike most work for the batch retrofit problem, a multiperiod disjunctive model is presented, such that long term investments and expansions can be planned out in advance. To solve the model we propose a rolling horizon algorithm that further exploits the advantages of a disjunctive programming model. Empirical work shows that the rolling horizon algorithm is very effective on finding near optimal solutions to large instances with a considerable number of time periods. Furthermore, the solution found by the proposed algorithm can be used as a starting solution for the direct method to the original problem delivering a global optimal solution.

► Given a batch plant, modular expansions are wanted so that new demands can be met.
► A multi-period disjunctive model is presented.
► The disjunctive model is solved by a rolling horizon algorithm.
► Near optimal solutions to large instances are found.