Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Multiple-Shooting Optimization using the JModelica.org Platform

Rantil, Jens ; Åkesson, Johan LU ; Führer, Claus LU and Gäfvert, Magnus LU (2009) 7th International Modelica Conference, 2009
Abstract
Dynamic optimization is the problem of finding the minimum of a cost function subject to a constraint comprised of a system of differential equations. There are many algorithms to numerically solve such optimization problems. One such algorithm is multiple shooting. This paper reports an implementation of a multiple shooting algorithm in Python. The implementation is based on the open source platform JModelica.org, the integrator SUNDIALS and the optimization algorithm scipy_slsqp. The JModelica.org platform supports model descriptions encoded in the Modelica language and optimization specifications expressed in the extension Optimica. The Modelica/Optimica combination provides simple means to express complex optimization problems in a... (More)
Dynamic optimization is the problem of finding the minimum of a cost function subject to a constraint comprised of a system of differential equations. There are many algorithms to numerically solve such optimization problems. One such algorithm is multiple shooting. This paper reports an implementation of a multiple shooting algorithm in Python. The implementation is based on the open source platform JModelica.org, the integrator SUNDIALS and the optimization algorithm scipy_slsqp. The JModelica.org platform supports model descriptions encoded in the Modelica language and optimization specifications expressed in the extension Optimica. The Modelica/Optimica combination provides simple means to express complex optimization problems in a compact and user-oriented manner. The JModelica.org platform, in turn translates the high-level descriptions into efficient C code which can compiled and linked with Python. As a result, the numerical packages available for Python can be used to develop custom applications based on Modelica/Optimica specifications. An example is provided to illustrate the capabilities of the method. (Less)
Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Contribution to conference
publication status
published
subject
conference name
7th International Modelica Conference, 2009
conference location
Como, Italy
conference dates
2009-09-20 - 2009-09-22
project
LCCC
Numerical Analysis and Scientific Computing
language
English
LU publication?
yes
additional info
The information about affiliations in this record was updated in December 2015. The record was previously connected to the following departments: Numerical Analysis (011015004), Department of Automatic Control (011017000)
id
d4603934-936b-4a8b-98b2-9d8dcda237e1 (old id 1625389)
date added to LUP
2016-04-04 13:53:10
date last changed
2026-02-23 15:13:33
@misc{d4603934-936b-4a8b-98b2-9d8dcda237e1,
  abstract     = {{Dynamic optimization is the problem of finding the minimum of a cost function subject to a constraint comprised of a system of differential equations. There are many algorithms to numerically solve such optimization problems. One such algorithm is multiple shooting. This paper reports an implementation of a multiple shooting algorithm in Python. The implementation is based on the open source platform JModelica.org, the integrator SUNDIALS and the optimization algorithm scipy_slsqp. The JModelica.org platform supports model descriptions encoded in the Modelica language and optimization specifications expressed in the extension Optimica. The Modelica/Optimica combination provides simple means to express complex optimization problems in a compact and user-oriented manner. The JModelica.org platform, in turn translates the high-level descriptions into efficient C code which can compiled and linked with Python. As a result, the numerical packages available for Python can be used to develop custom applications based on Modelica/Optimica specifications. An example is provided to illustrate the capabilities of the method.}},
  author       = {{Rantil, Jens and Åkesson, Johan and Führer, Claus and Gäfvert, Magnus}},
  language     = {{eng}},
  title        = {{Multiple-Shooting Optimization using the JModelica.org Platform}},
  url          = {{https://lup.lub.lu.se/search/files/6228482/8147227.pdf}},
  year         = {{2009}},
}