A direct transcription-based multiple shooting formulation for dynamic optimization. (2nd September 2020)

• Record Type: Journal Article
• Authors: Kelley, Morgan T.; Baldick, Ross; Baldea, Michael
• Is Part Of: Computers & chemical engineering. Volume 140(2020)
• Publication Date: 2020-09-02
• Subjects: Dynamic optimization -- Multiple shooting -- Direct transcription; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2020.106846
• Languages: English
• ISSNs: 0098-1354

Abstract

Highlights: General framework for dynamic optimization of nonlinear systems. Discrete multiple-shooting formulation eliminates repeated time integration. Lagrangian relaxation scheme allows fast computation. Abstract: The growing need for fast and efficient solution techniques for solving dynamic optimization problems is driven by a broad spectrum of applications in scheduling and control. We propose a novel framework for dynamic optimization that utilizes a multiple shooting "backbone" with discrete rather than continuous subproblems, thereby eliminating need for repeated time-integration. A Lagrangian relaxation (LR)-based decomposition scheme is proposed, which dualizes the state continuity requirements between subproblems and enables parallel solution of the problem. We demonstrate the applicability of our method on two case studies: the Van der Pol oscillator and a batch reactor.