PyOpt: a python-based object-oriented framework for nonlinear constrained optimization

DOI10.1007/s00158-011-0666-3zbMath1274.90008OpenAlexW2012884505WikidataQ121224427 ScholiaQ121224427MaRDI QIDQ381697

Joaquim R. R. A. Martins, Ruben E. Perez, Peter W. Jansen

Publication date: 15 November 2013

Published in: Structural and Multidisciplinary Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00158-011-0666-3

zbMATH Keywords

constrained optimizationnonlinear programmingobject-oriented programmingoptimization algorithms\texttt{PyOpt}aerostructural optimizationpython

Mathematics Subject Classification ID

Nonlinear programming (90C30) Software, source code, etc. for problems pertaining to operations research and mathematical programming (90-04)

Related Items (16)

A matrix-free augmented Lagrangian algorithm with application to large-scale structural design optimization ⋮ An aerodynamic design optimization framework using a discrete adjoint approach with OpenFOAM ⋮ Stress-constrained topology optimization with design-dependent loading ⋮ Stress-based structural topology optimization for design-dependent self-weight loads problems using the BESO method ⋮ Efficient Matlab implementation of NURBS-based IGA and material design using isogeometric topology optimization ⋮ Progressive construction of a parametric reduced‐order model for PDE‐constrained optimization ⋮ Effective transient behaviour of inclusions in diffusion problems ⋮ Structural topology optimization with design-dependent pressure loads ⋮ An optimization-based approach for high-order accurate discretization of conservation laws with discontinuous solutions ⋮ PyFly: a fast, portable aerodynamics simulator ⋮ Realization of a framework for simulation-based large-scale shape optimization using vertex morphing ⋮ A sequential quadratic programming algorithm for equality-constrained optimization without derivatives ⋮ Reinforcement-learning-based control of confined cylinder wakes with stability analyses ⋮ pyOpt ⋮ Compressibility effects on the structural evolution of transitional high-speed planar wakes ⋮ Design optimization for self-propulsion of a bulk carrier hull using a discrete adjoint method

Uses Software

• SNOPT
• AMPL
• TOMLAB
• CVXOPT
• SolvOpt
• CVX
• YALMIP
• F2PY
• COIN-OR
• CONMIN
• Pyomo
• AIMMS
• COOPR
• OpenOpt
• PuLP
• pyipopt
• PySP
• GAMS
• DAKOTA
• OPT++
• SciPy
• pyMDO
• NLPQL
• TAO
• Decision tree for optimization software
• Python
• SciTools
• OpenMDAO
• DFVLR-SQP

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Benchmarking multidisciplinary design optimization algorithms
• The oracle penalty method
• Extended ant colony optimization for non-convex mixed integer nonlinear programming
• More test examples for nonlinear programming codes
• Test examples for nonlinear programming codes
• Methods of descent for nondifferentiable optimization
• A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice
• pyMDO
• The method of moving asymptotes—a new method for structural optimization
• SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization
• An SQP Algorithm for Finely Discretized Continuous Minimax Problems and Other Minimax Problems with Many Objective Functions
• The complex-step derivative approximation

This page was built for publication: PyOpt: a python-based object-oriented framework for nonlinear constrained optimization