The Computational Complexity Analysis of a MINLP-Based Chemical Process Control Design
Abstract
It is essential that a chemical process plant is built based on a design that integrates the structural, operational and economic considerations. However, accomplishing such goal for a small section of a process system demands significant computational efforts. This project investigates the computational tractability of a mathematical optimization algorithm dedicated for such process control design, the Dynamic Operability Framework. The target output is a worst case computational cost of utilizing the framework to solve a process control design problem in comparison with a standard Mixed Integer Non-Linear Programming (MINLP) problem. The cost is calculated based on the numbers of design variables and constraints. This cost helps process designers to make an informed decision of utilizing and improving the framework as a tool for process design
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