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.

结晶系统的多目标优化（MOO）越来越重要，因为它能够共同处理多个相互矛盾的目标，以找到最佳的运行策略。本研究集中于柠檬酸的分批冷却结晶。在两种形式的柠檬酸中，选择柠檬酸酐（CAA）进行实验，因为尚无此类研究。进行MOO是为了寻求CAA的非种子冷却结晶的最佳冷却策略，以使平均晶体尺寸最大化，同时使尺寸差异最小。在该过程中，使用分段恒定控制矢量参数化来离散温度，这对于实际实现而言是简单且方便的。文献中报道的模型已针对溶解度参数进行了适当修改，这些参数已通过实验验证，并进行了优化。通过实验成功地实现了帕累托解决方案集中的最佳解决方案之一，并且所测得的产品晶体性能与通过优化获得的预测结果具有可比性。