![]() Lb: Variable lower bound vector (optional). knitro_lp ( f, A, b, Aeq, beq, lb, ub, x0, extendedFeatures, options, knitroOptsFile )Ī: Coefficient matrix for linear inequality constraints.ī: Upper bound vector for linear inequality constraints.Īeq: Coefficient matrix for linear equality constraints (optional).īeq: Right-hand side vector for linear equality constraints (optional). The knitromatlab/examples directory provided with the Knitro distribution. Several examples using both the solver-based approach and problem-based approach are included in The Knitro/MATLAB interface functions are described in more detail below in alphabetical order. In addition, the knitro_options function can be used to specify Knitro solver The Knitro/MATLAB interface also provides a generic knitro_solve function that canīe used to solve any model defined using the problem-based approach. Knitro_qp for solving quadratic programs (QPs). Knitro_qcqp for solving quadratically constrained quadratic programs (QCQPs) (this function can also be used to solve second order cone programs (SOCPs) by formulating the cone constraints as quadratic constraints) Knitro_nlp for solving continuous nonlinear optimization models (NLPs) Knitro_nlnlsq for solving nonlinear least-squares models Knitro_nlneqs for solving nonlinear systems of equations Knitro_minlp for solving mixed-integer nonlinear optimization models (MINLPs) Knitro_milp for solving mixed-integer linear programs (MILPs) Knitro_lp for solving linear programs (LPs) The solver-based interface provides the following specialized functionĬalls for various optimization model types: The “solver-based” and “problem-based” approaches offered by MATLAB. The interfaces used to call Knitro from the MATLAB environment mimic both ![]()
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