A novel optimization framework based on a stochastic optimization algorithm is proposed for optimizing batch, semi-batch and non-isothermal evaporative crystallizations. The mathematical models for these dynamic processes are highly non-linear and hence involve prominent non-convexities in the solution space of optimization. The framework not only significantly reduces the likelihood of being trapped into local optima and convergence problems in optimization and simulations, but also employs a novel and efficient algorithm for optimization of control profiles. A new concept in combining heating/cooling and evaporation in a batch crystallization operation is also proposed in this work. Optimization results of the citric acid-water system using this concept indicate that the maximum average crystal size obtainable is 19% and 27% larger than those attainable in the optimized unseeded evaporative and cooling operations respectively. The crystal size distribution is significantly narrower than that under seeded operations. Yield increase of more than 42% is also observed in this operating methodology. Optimization results for the batch and semi-batch evaporative crystallizations also demonstrate improvements that otherwise cannot be attained by using conventional approaches and heuristic rules. (C) 2003 Elsevier Ltd. All rights reserved.