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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Vydáno v:Optimization letters Ročník 13; číslo 7; s. 1505 - 1514
Hlavní autor: Kanno, Yoshihiro
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2019
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ISSN:1862-4472, 1862-4480
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Abstract 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.
AbstractList 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.
Author Kanno, Yoshihiro
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  organization: Mathematics and Informatics Center, The University of Tokyo
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Cites_doi 10.1007/s00466-017-1440-1
10.1007/s13160-018-0323-y
10.1016/j.compstruc.2017.07.031
10.1016/j.cma.2017.11.013
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Keywords Model-free computational mechanics
Global optimization
Data-driven computing
Mixed-integer programming
Exact solution method
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Mathematics
Mathematics and Statistics
Numerical and Computational Physics
Operations Research/Decision Theory
Optimization
Original Paper
Simulation
Title Mixed-integer programming formulation of a data-driven solver in computational elasticity
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