Robust generation of constrained B-spline curves based on automatic differentiation and fairness optimization

DOI10.1016/j.cagd.2017.11.005zbMath1381.65011OpenAlexW2775131451MaRDI QIDQ1693676

T. Luke McCulloch, Lothar Birk

Publication date: 31 January 2018

Published in: Computer Aided Geometric Design (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cagd.2017.11.005

zbMATH Keywords

constrained optimizationcomputer aided designautomatic differentiationB-splinePythoncurve designcomputer aided engineeringcomputer aided ship hull designfairness optimizationform parameter design

Mathematics Subject Classification ID

Numerical computation using splines (65D07) Numerical differentiation (65D25) Computer-aided design (modeling of curves and surfaces) (65D17)

Uses Software

• Theano
• CasADi
• Python
• PyCppAD
• PyADOL-C
• AlgoPy
• pyadolc
• ad

Cites Work

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• Five decades of computer-aided ship design
• Linear and nonlinear programming.
• Solving nonlinear eigenvalue problems by algorithmic differentiation
• A practical guide to splines
• On calculating with B-splines
• Encyclopedia of Optimization
• Introduction to Automatic Differentiation and MATLAB Object-Oriented Programming
• Automatic Hessians by reverse accumulation
• Automatic differentiation of numerical integration algorithms
• The Numerical Evaluation of B-Splines

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