APOPT explained

APOPT
Latest Release Version:	1.0.4
Genre:	Technical computing
License:	Proprietary

APOPT (for Advanced Process OPTimizer) is a software package for solving large-scale optimization problems of any of these forms:

• Linear programming (LP)
• Quadratic programming (QP)
• Quadratically constrained quadratic program (QCQP)
• Nonlinear programming (NLP)
• Mixed integer programming (MIP)
• Mixed integer linear programming (MILP)
• Mixed integer nonlinear programming (MINLP)

Applications of the APOPT include chemical reactors,^{[1] [2]} friction stir welding,^[3] prevention of hydrate formation in deep-sea pipelines,^{[4] [5]} computational biology,^[6] solid oxide fuel cells,^{[7] [8]} and flight controls for Unmanned Aerial Vehicles (UAVs).^[9]

Benchmark Testing

Standard benchmarks such as CUTEr and SBML curated models are used to test the performance of APOPT relative to solvers BPOPT, IPOPT, SNOPT, and MINOS. A combination of APOPT (Active Set SQP) and BPOPT (Interior Point Method) performed the best on 494 benchmark problems for solution speed and total fraction of problems solved.^[10]

See also

• APOPT is supported in AMPL, APMonitor, Gekko, Julia, MATLAB, Pyomo, and Python.

External links

• • Web interface to solve optimization problems with the APOPT solver
• Download APOPT for AMPL, MATLAB, Julia, Python, or APMonitor

Notes and References

1. WO . 2012005740 . patent . Method for Controlling Bubble Formation in Polymerization Reactors . 2012-01-12 . Lawson, K. W., Hedengren, J. D., Smith, L. C..
2. Spivey . B. . Constrained Nonlinear Estimation for Industrial Process Fouling . Industrial & Engineering Chemistry Research . 49 . 17 . 7824–7831 . 2010 . 10.1021/ie9018116.
3. M.Sc. . Isak . Nielsen . Modeling and Control of Friction Stir Welding in 5 cm thick Copper Canisters . Linköping University . 2012 .
4. Brower . D. . Fiber Optic Monitoring of Subsea Equipment . OMAE 2012 Proceedings, Rio de Janeiro, Brazil . 2012 .
5. Brower . D. . Advanced Deepwater Monitoring System . OMAE 2013 Proceedings, Nantes, France . 2013 .
6. Abbott . C. . New Capabilities for Large-Scale Models in Computational Biology . AIChE Annual Meeting Proceedings, Pittsburgh, PA . 2012 .
7. Spivey . B. . Dynamic Modeling of Reliability Constraints in Solid Oxide Fuel Cells and Implications for Advanced Control . AIChE Annual Meeting Proceedings, Salt Lake City, Utah . 2010 .
8. Jacobsen . L. . Model Predictive Control with a Rigorous Model of a Solid Oxide Fuel Cell . American Control Conference (ACC), Washington, DC . 2013 .
9. Sun . L. . Optimal Trajectory Generation using Model Predictive Control for Aerially Towed Cable Systems . Journal of Guidance, Control, and Dynamics . 2013 .
10. Hedengren . J. . APOPT: MINLP Solver for Differential Algebraic Systems with Benchmark Testing . INFORMS Annual Meeting . 2012 .