A direct transcription-based multiple shooting formulation for dynamic optimization

Kelley, Morgan T.; Baldick, Ross; Baldea, Michael

doi:10.1016/j.compchemeng.2020.106846

Title: A direct transcription-based multiple shooting formulation for dynamic optimization

Journal Article · Sat May 30 00:00:00 EDT 2020 · Computers and Chemical Engineering

DOI:https://doi.org/10.1016/j.compchemeng.2020.106846· OSTI ID:1800882

Kelley, Morgan T. ^[1]; Baldick, Ross ^[2]; Baldea, Michael ^[1]

McKetta Department of Chemical Engineering, Austin, TX (United States)
Univ. of Texas, Austin, TX (United States)

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 suggest 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.

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Research Organization:: Krell Institute, Ames, IA (United States); Univ. of Texas at Austin, TX (United States)

Sponsoring Organization:: USDOE Office of Science (SC); National Science Foundation (NSF)

Grant/Contract Number:: FG02-97ER25308; OE0000841; 1454433; CBET-1512379

OSTI ID:: 1800882

Alternate ID(s):: OSTI ID: 1631352; OSTI ID: 1872915

Journal Information:: Computers and Chemical Engineering, Vol. 140, Issue C; ISSN 0098-1354

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 7 works

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