qp_1.py

Revision 1408, 0.8 kB (checked in by dmitrey.kroshko, 2 months ago)
qp2nlp converter + minor changes

Line
1	"""
2	Example:
3	Concider the problem
4	0.5 * (x1^2 + 2x2^2 + 3x3^2) + 15x1 + 8x2 + 80x3 -> min (1)
5	subjected to
6	x1 + 2x2 + 3x3 <= 150 (2)
7	8x1 + 15x2 + 80x3 <= 800 (3)
8	x2 - x3 = 25 (4)
9	x1 <= 15 (5)
10	"""
11
12	from numpy import diag, matrix, inf
13	from scikits.openopt import QP
14	p = QP(diag([1,2,3]), [15,8,80], A = matrix('1 2 3; 8 15 80'), b = [150, 800], Aeq = [0, 1, -1], beq = 25, ub = [15,inf,inf])
15	# or p = QP(H=diag([1,2,3]), f=[15,8,80], A = matrix('1 2 3; 8 15 80'), b = [150, 800], Aeq = [0, 1, -1], beq = 25, ub = [15,inf,inf])
16	r = p.solve('cvxopt_qp', iprint = 0)
17	# r = p.solve('nlp:ipopt'), r = p.solve('nlp:algencan')
18	f_opt, x_opt = r.ff, r.xf
19	# x_opt = array([-14.99999995, -2.59999996, -27.59999991])
20	# f_opt = -1191.90000013

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