Description

Minimize the time take for a particle, acted upon by a thrust of
constant magnitude, to achieve a given altitude and terminal
velocity.

This model is from the COPS benchmarking suite.
See http://www-unix.mcs.anl.gov/~more/cops/.

The number of discretization points can be specified using the command
line parameter --nh. COPS performance tests have been reported for nh
= 50, 100, 200, 400

Large Model of Type : NLP

Category : GAMS Model library

Main file : lnts.gms

$title Particle steering COPS 2.0 #9 (LNTS,SEQ=237)

$onText
Minimize the time take for a particle, acted upon by a thrust of
constant magnitude, to achieve a given altitude and terminal
velocity.

This model is from the COPS benchmarking suite.
See http://www-unix.mcs.anl.gov/~more/cops/.

The number of discretization points can be specified using the command
line parameter --nh. COPS performance tests have been reported for nh
= 50, 100, 200, 400


Dolan, E D, and More, J J, Benchmarking Optimization
Software with COPS. Tech. rep., Mathematics and Computer
Science Division, 2000.

Betts, J, Eldersveld, S, and Huffman, W, Sparse
Nonlinear Programming Test Problems. Tech. rep.,
Boeing Computer Services, 1993.

Bryson, A, and Ho, Y, Applied Optimal Control:
Optimization, Estimation, and Control. John Wiley and Sons,
1975.

Keywords: nonlinear programming, engineering, particle steering
$offText

$if not set nh $set nh 50

Set
   h 'intervals'   / h0*h%nh% /
   c 'coordinates' / y1 'first position coordinate'
                     y2 'second position coordinate'
                     y3 'first velocity coordinate'
                     y4 'second velocity coordinate' /;

Scalar
   nh 'number of intervals' / %nh%  /
   a  'magnitude of force'  / 100.0 /;

Variable
   u(h)   'control'
   y(c,h) 'coordinates'
   tf     'final time';

Positive Variable step 'step size';

Equation
   tf_eqn
   pos_eqn(c,h)
   velo1_eqn(h)
   velo2_eqn(h);

tf_eqn.. tf =e= step*nh;

pos_eqn(c+2,h+1).. y(c,h+1)  =e= y(c,h) + 0.5*step*(y(c+2,h) + y(c+2,h+1));

velo1_eqn(h+1).. y('y3',h+1) =e= y('y3',h) + 0.5*step*(a*cos(u(h)) + a*cos(u(h+1)));

velo2_eqn(h+1).. y('y4',h+1) =e= y('y4',h) + 0.5*step*(a*sin(u(h)) + a*sin(u(h+1)));

u.lo(h) = -pi/2;
u.up(h) =  pi/2;

y.fx(c,'h0')       =  0;
y.fx('y2','h%nh%') =  5;
y.fx('y3','h%nh%') = 45;
y.fx('y4','h%nh%') =  0;

step.l      = 1.0/nh;
y.l('y2',h) =  5*(ord(h)-1)/nh;
y.l('y3',h) = 45*(ord(h)-1)/nh;

Model lnts / all /;

$if set workSpace lnts.workSpace = %workSpace%

solve lnts using nlp minimizing tf;