Difference between revisions of "Lotka Volterra fishing problem (TACO)"

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(Lotka model using AMPL and TACO)
 
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== Source Code ==
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Other model descriptions are available in
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* Mathematical notation at [[Lotka Volterra fishing problem]]
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* [[:Category:AMPL | AMPL]] (using a fixed discretization) at [[Lotka Volterra fishing problem (AMPL)]]
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* [[:Category:C | C code]] at [[Lotka Volterra fishing problem (C)]]
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* [[:Category:optimica | optimica]] at [[Lotka Volterra fishing problem (optimica)]]
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[[Category:AMPL]]
 
[[Category:AMPL]]

Revision as of 23:17, 28 September 2011

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. 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;

Source Code

Other model descriptions are available in

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