Mixed-integer programming formulation of a data-driven solver in computational elasticity

This paper presents a mixed-integer quadratic programming formulation of an existing data-driven approach to computational elasticity. This formulation is suitable for application of a standard mixed-integer programming solver, which finds a global optimal solution. Therefore, the results obtained b...

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Veröffentlicht in:	Optimization letters Jg. 13; H. 7; S. 1505 - 1514
1. Verfasser:	Kanno, Yoshihiro
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2019
Schlagworte:	Computational Intelligence Mathematics Mathematics and Statistics Numerical and Computational Physics Operations Research/Decision Theory Optimization Original Paper Simulation Model-free computational mechanics Global optimization Data-driven computing Mixed-integer programming Exact solution method
ISSN:	1862-4472, 1862-4480
Online-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	This paper presents a mixed-integer quadratic programming formulation of an existing data-driven approach to computational elasticity. This formulation is suitable for application of a standard mixed-integer programming solver, which finds a global optimal solution. Therefore, the results obtained by the presented method can be used as benchmark instances for any other algorithm. Preliminary numerical experiments are performed to compare quality of solutions obtained by the proposed method and a heuristic conventionally used in the data-driven computational mechanics.
ISSN:	1862-4472 1862-4480
DOI:	10.1007/s11590-019-01409-w