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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Bibliographic Details
Published in:Optimization letters Vol. 13; no. 7; pp. 1505 - 1514
Main Author: Kanno, Yoshihiro
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2019
Subjects:
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 Access:Get full text
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Summary: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