Package pypower :: Module qps_cplex
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Module qps_cplex

source code

Quadratic Program Solver based on CPLEX.

Functions [hide private]
 
qps_cplex(H, c, A, l, u, xmin, xmax, x0, opt)
Quadratic Program Solver based on CPLEX.
source code
Variables [hide private]
  EPS = 2.2204460492503131e-16
  __package__ = 'pypower'
Function Details [hide private]

qps_cplex(H, c, A, l, u, xmin, xmax, x0, opt)

source code 

Quadratic Program Solver based on CPLEX.

A wrapper function providing a PYPOWER standardized interface for using cplexqp or cplexlp to solve the following QP (quadratic programming) problem:

   min 1/2 X'*H*x + c'*x
    x

subject to:

   l <= A*x <= u       (linear constraints)
   xmin <= x <= xmax   (variable bounds)

Inputs (all optional except H, c, A and l):

  • H : matrix (possibly sparse) of quadratic cost coefficients
  • c : vector of linear cost coefficients
  • A, l, u : define the optional linear constraints. Default values for the elements of L and U are -Inf and Inf, respectively.
  • xmin, xmax : optional lower and upper bounds on the x variables, defaults are -Inf and Inf, respectively.
  • x0 : optional starting value of optimization vector x
  • opt : optional options structure with the following fields, all of which are also optional (default values shown in parentheses)
    • verbose (0) - controls level of progress output displayed
      • 0 = no progress output
      • 1 = some progress output
      • 2 = verbose progress output
    • cplex_opt - options dict for CPLEX, value in verbose overrides these options
  • problem : The inputs can alternatively be supplied in a single problem dict with fields corresponding to the input arguments described above: H, c, A, l, u, xmin, xmax, x0, opt

Outputs:

  • x : solution vector
  • f : final objective function value
  • exitflag : CPLEXQP/CPLEXLP exit flag (see cplexqp and cplexlp documentation for details)
  • output : CPLEXQP/CPLEXLP output dict (see cplexqp and cplexlp documentation for details)
  • lmbda : dict containing the Langrange and Kuhn-Tucker multipliers on the constraints, with fields:
    • mu_l - lower (left-hand) limit on linear constraints
    • mu_u - upper (right-hand) limit on linear constraints
    • lower - lower bound on optimization variables
    • upper - upper bound on optimization variables
Authors:
Ray Zimmerman (PSERC Cornell), Richard Lincoln