MINLP
From OpenOpt
Mixed-Integer Non-Linear Problems (MINLP)
- subjected to
- (smooth differentiable functions)
- OpenOpt MINLP example
-
FuncDesigner MINLP examples:
- simple (with automatic differentiation)
- example with specifiable accuracy (via interval analysis by interalg)
MINLP solvers connected to OpenOpt:
Solver | License | Algorithm | Authors | Info |
---|---|---|---|---|
(since v. 0.38) interalg |
BSD | an interval algorithm | Dmitrey | searches global extremum with specifiable accuracy fTol: abs(f - f*) < fTol , where f* is theoretical optimal value. Can handle nonsmooth, multiextremum and even some discontinuous funcs like ceil, floor. |
branb | BSD | branch-and-bound | Ingar Solberg, Institutt for teknisk kybernetikk, Norges Tekniske Hrgskole, Norway | This is translation of MATLABs fminconset routine to Python (by Dmitrey, with some minor changes). It recuires parameter "nlpSolver" like "ipopt', "scipy_lbfgsb", "scipy_tnc" etc for solving NLP subproblems. |
Note!
- MINLP is NP-Hard class of problems.
- Please pay attention: objective function and non-linear constraints should be defined in whole R^nVars, i.e. for discrete variables as well as for continuous.
- For branb It is assumed that objective function and constraints are at least unimodal (convex is preferred).
See also: