Multiobjective optimization (MOO) of crystallization systems is gaining importance due to its ability to handle multiple conflicting objectives together for finding optimal operating policies. The present study focuses on batch cooling crystallization of citric acid. Among the two forms of citric acid, citric acid anhydride (CAA) is chosen for experimentation as no such study is available. MOO is carried out to seek optimal cooling policy for unseeded cooling crystallization of CAA to maximize mean crystal size while minimizing variance in size. In this procedure, temperature is discretized using piecewise constant-control vector parameterization which is simple and convenient for practical implementation. The model reported in literature is suitably modified for solubility parameters which are verified experimentally, and employed for optimization. One of the optimal solutions from the Pareto solution set is implemented through experimentation successfully and the measured product crystal properties are comparable to the predicted results obtained through optimization. (c) 2018 Elsevier Ltd. All rights reserved.