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