An algorithm that employs the back‐off method to provide optimal solutions for integration of design, control, and scheduling for multiproduct systems is presented, featuring a flexibility and feasibility analysis. The algorithm employs Monte Carlo (MC) sampling to generate a large number of random realizations, and simulate the system to determine feasibility. Back‐off terms are determined and incorporated into a new flexibility analysis to approximate the effect of stochastic uncertainty and disturbances. Through successive iterations, the algorithm converges, terminating on a solution that is robust to a specified level of process variability due to stochastic realizations in the disturbances and uncertain parameters. The proposed algorithm has been successfully applied to a multiproduct continuous stirred tank reactor for which optimal design, control, and scheduling decisions are identified, subject to stochastic uncertainty and disturbance. The present approach has been compared to a critical‐set (multiscenario) method showing the benefits and limitations of both approaches. © 2018 American Institute of Chemical Engineers AIChE J, 64: 2379–2389, 2018

中文翻译：

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不确定环境下用于多产品系统的同时设计，控制和调度的随机后退算法

提出了一种利用后退方法为多产品系统的设计，控制和调度集成提供最佳解决方案的算法，该算法具有灵活性和可行性分析功能。该算法采用蒙特卡洛（MC）采样生成大量随机实现，并对系统进行仿真以确定可行性。确定退避条件并将其纳入新的灵活性分析中，以近似随机不确定性和干扰的影响。通过连续的迭代，该算法收敛，最终得出了由于干扰和不确定参数的随机实现而对指定的过程可变性具有鲁棒性的解决方案。所提出的算法已成功应用于多产品连续搅拌釜反应器，其最佳设计，受到随机不确定性和干扰的影响，确定控制和调度决策。本方法已与关键集（多方案）方法进行了比较，显示了这两种方法的优点和局限性。©2018美国化学工程师学会AIChE J，64：2379–2389，2018