A multicut generalized benders decomposition approach for the integration of process operations and dynamic optimization for continuous systems

The integration of process operations and dynamic optimization leads to large scale optimization problems whose monolithic solution is challenging. In this paper we propose a new formulation of the integrated planning, scheduling, and dynamic optimization problem for continuous single stage systems. We analyze the structure of the problem using Stochastic Blockmodeling and we show that the estimated structure can be used as the basis for a multicut Generalized Benders decomposition (GBD) algorithm, which can solve the problem in reduced computational time. Furthermore, we propose an accelerated hybrid multicut algorithm which can lead to further reduction in computational time. Through case studies, we analyze the computational performance of the proposed formulation and decomposition based solution algorithms.

Automated summary

This paper proposes a new solution for the integrated planning, scheduling, and dynamic optimization problem in continuous single stage systems. By analyzing the problem structure and introducing the algorithm, an accurate solution can be obtained in a shorter computation time.