Difference between revisions of "Lotka Volterra fishing problem (TACO)"
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− | This page contains a model of the MIOCP [[Lotka Volterra fishing problem]] in [http://www.ampl.org AMPL] format, making use of the TACO toolkit for AMPL control optimization extensions. This problem is due to < | + | This page contains a model of the MIOCP [[Lotka Volterra fishing problem]] in [http://www.ampl.org AMPL] format, making use of the TACO toolkit for AMPL control optimization extensions. This problem is due to <bib id="Sager2005" />. |
Note that you will need to include a generic [[support AMPL files|AMPL/TACO support file]], OptimalControl.mod. | Note that you will need to include a generic [[support AMPL files|AMPL/TACO support file]], OptimalControl.mod. | ||
To solve this model, you require an optimal control or MINLP code that uses the TACO toolkit to support the AMPL optimal control extensions. | To solve this model, you require an optimal control or MINLP code that uses the TACO toolkit to support the AMPL optimal control extensions. | ||
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</source> | </source> | ||
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== References == | == References == | ||
− | < | + | <biblist /> |
[[Category:AMPL/TACO]] | [[Category:AMPL/TACO]] |
Latest revision as of 10:25, 28 January 2016
This page contains a model of the MIOCP Lotka Volterra fishing problem in AMPL format, making use of the TACO toolkit for AMPL control optimization extensions. This problem is due to [Sager2005]Address: Tönning, Lübeck, Marburg
Author: S. Sager
Editor: ISBN 3-89959-416-9
Publisher: Der andere Verlag
Title: Numerical methods for mixed--integer optimal control problems
Url: http://mathopt.de/PUBLICATIONS/Sager2005.pdf
Year: 2005
.
Note that you will need to include a generic AMPL/TACO support file, OptimalControl.mod.
To solve this model, you require an optimal control or MINLP code that uses the TACO toolkit to support the AMPL optimal control extensions.
AMPL
This is the source file lotka_taco.mod
# ---------------------------------------------------------------- # Lotka Volterra fishing problem using AMPL and TACO # (c) Christian Kirches, Sven Leyffer # ---------------------------------------------------------------- include OptimalControl.mod; var t; var xd0 := 0.5, >= 0, <= 20; var xd1 := 0.7, >= 0, <= 20; var dev := 0.0, >= 0, <= 20; var u := 1, >= 0, <= 1 integer suffix type "u0"; param p0 := 0.4; param p1 := 0.2; param ref0 := 1.0; param ref1 := 1.0; # Minimize accumulated deviation from reference after 12 time units minimize Mayer: eval(dev,12); subject to # ODE system ODE_0: diff(xd0,t) = xd0 - xd0*xd1 - p0*u*xd0; # prey ODE_1: diff(xd1,t) = -xd1 + xd0*xd1 - p1*u*xd1; # predator ODE_2: diff(dev,t) = (xd0-ref0)^2 + (xd1-ref1)^2; # deviation from reference # initial value constraints IVC_0: eval(xd0,0) = 0.5; IVC_1: eval(xd1,0) = 0.7; IVC_2: eval(dev,0) = 0.0; option solver ...; solve;
References
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