AbstractA multiperiod mixed‐integer nonlinear programming (MINLP) optimization model is presented to schedule catalyst changeovers and determine the best operating policy for a chemical process with decaying performance. Two solution strategies are proposed to reduce the effect of nonconvexities and to reduce the solution time: (1) a search strategy that relies on partitioning the time horizon and (2) a strategy that makes use of the Generalized Benders Decomposition (GBD). Examples are presented for different time horizons to illustrate the performance of the proposed methods. The same objective value is reached with both strategies, which find better solutions than the full‐space MINLP. For small models, the GBD algorithm is faster than the partitioning search strategy, whereas the latter method is faster for larger models. Comparison with the operating strategy used in a real plant is also presented. © 2005 American Institute of Chemical Engineers AIChE J, 51:909–921, 2005