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MIDACO on MINLP Space Applications

Martin Schlueter(info***at***midaco-solver.com)
Sven Erb(sven.erb***at***esa.int)
Matthias Gerdts(matthias.gerdts***at***unibw.de)
Steven Kemble(Stephen.KEMBLE***at***astrium.eads.net)
Jan Joachim Rueckmann(j.ruckmann***at***bham.ac.uk)

Abstract: A numerical study on two challenging MINLP space applications and their optimization with MIDACO, which is a recently developed general purpose optimization software, is pre- sented. The applications are in particular the optimal control of the ascent of a multiple-stage space launch vehicle and the space mission trajectory design from Earth to Jupiter using mul- tiple gravity assists. Additionally an NLP aerospace application, the optimal control of an F8 aircraft manoeuvre, is furthermore discussed and solved. In order to enhance the opti- mization performance of MIDACO a hybridization technique, coupling MIDACO with a SQP algorithm, is presented for two of the three applications. The numerical results show, that the applications can be solved to their best known solution (or even new best solutions) in a reasonable time by the here considered approach. As the concept of MINLP is still a novelty in the field of (aero)space engineering, the here demonstrated capabilities are seen as promising.

Keywords: MIDACO, MINLP, NLP, SQP, Hybrid Optimization, Space Application

Category 1: Applications -- Science and Engineering

Category 2: Integer Programming ((Mixed) Integer Nonlinear Programming )

Category 3: Convex and Nonsmooth Optimization (Nonsmooth Optimization )

Citation: Advances in Space Research (Elsevier), Vol 51, Issue 7, Pages 1116–1131 (2013)

Download: [PDF]

Entry Submitted: 05/06/2013
Entry Accepted: 05/06/2013
Entry Last Modified: 05/06/2013

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