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Optimization-based design of reactive distillation columns using a memetic algorithm

机译：基于模因算法的反应精馏塔优化设计

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摘要

The design optimization of reactive distillation columns (RDC) is characterized by complex nonlinear constraints, nonlinear cost functions, and the presence of many local optima. The standard approach is to use MINLP solvers that work on a superstructure formulation where structural decisions are represented by discrete variables and lead to an exponential increase in the computational effort. The mathematical programming (MP) methods which solve the continuous sub-problems provide only one local optimum which depends strongly on the initialization. In this contribution a memetic algorithm (MA) is introduced and applied to the global optimization of four different formulations of a computational demanding real-world design problem. An evolution strategy addresses the global optimization of the design decisions, while continuous sub-problems are efficiently solved by a robust MP solver. The MA is compared to MINLP techniques. It is the only algorithm that finds the global solution in reasonable times for all model formulations.
机译：反应精馏塔（RDC）的设计优化具有复杂的非线性约束，非线性成本函数以及许多局部最优的特征。标准方法是使用MINLP求解器，该求解器用于上层结构公式化，其中结构决策由离散变量表示，并导致计算工作量呈指数增长。解决连续子问题的数学编程（MP）方法仅提供一个局部最优值，该最优值在很大程度上取决于初始化。在此贡献中，引入了模因算法（MA），并将其应用于对计算要求很高的实际设计问题的四种不同公式的全局优化。演化策略解决了设计决策的全局优化问题，而强大的MP求解器可有效解决连续子问题。将MA与MINLP技术进行比较。它是唯一可在合理时间内为所有模型公式找到全局解的算法。

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