Ignore:
Timestamp:
07/21/10 09:10:59 (6 years ago)
Author:
altafang
Message:

Found some good sources of optimization test problems, and translated some of them into Python.

File:
1 edited

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  • branches/alta/mystic-0.2a1/test_constraints_cvxopt_qp.py

    r334 r338  
    3636      x + y == 1.0}, {x, y}] 
    3737    Solution: {1.875, {x -> 0.25, y -> 0.75}} 
     38 
     39    OpenOpt code and results: 
     40    ------------------------- 
     41    from FuncDesigner import * 
     42    from openopt import NLP 
     43    x1, x2 = oovars ('x1', 'x2') 
     44    f = 2.*x1**2 + x2**2 + x1*x2 + x1 + x2 
     45    constraints = [x1 >= 0.0, x2 >= 0.0, x1 + x2 == 1.0] 
     46    x0 = {x1:1.,x2: 1.} 
     47    problem = NLP(f, x0, constraints=constraints) 
     48    soln = problem.solve('ralg') 
     49    print soln.xf 
     50    Solution: {x1: array([ 0.2500267]), x2: array([ 0.7499733])} 
    3851""" 
    3952 
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