1 : Maximum Number of Iterations Exceeded.The values it can take and what they indicate is described below: The exitflag allows the user to know the status of the optimization which is returned by Ipopt. Options = list("MaxIter",, "CpuTime", ) The default values for the various items are given as: It is declared in such a way that gradient of nonlinear inequality constraints are defined first as a separate Matrix (cg of size m2 X n or as an empty), followed by gradient of nonlinear equality constraints as a separate matrix (ceqg of size m2 X n or as an empty) where m2 & m3 are number of nonlinear inequality and equality constraints respectively. GradCon : A function, representing the gradient of the nonlinear Constraints (both Equality and Inequality) of the problem.Refer to Example 5 for definition of Lagrangian Hessian function. Hessian : A function, representing the hessian function of the Lagrange in the form of a Symmetric Matrix with Input parameters as x, Objective factor and Lambda.GradObj : A function, representing the gradient function of the Objective in vector form.CpuTime : A Scalar, specifying the maximum amount of CPU time in seconds that the solver should take.MaxIter : A Scalar, specifying the maximum number of iterations that the solver should take.The options should be defined as type "list" and consist of the following fields: Options= list("MaxIter",, "CpuTime",, "GradObj", -, "Hessian", -, "GradCon", -) OptionsThe options allow the user to set various parameters of the Optimization problem. Search the minimum of a constrained optimization problem specified by:įmincon calls Ipopt, an optimization library written in C++, to solve the Constrained Optimization problem. options :Ī list, containing the option for user to specify. It is declared in such a way that nonlinear inequality constraints (c), and the nonlinear equality constraints (ceq) are defined as separate single row vectors. nlc :Ī function, representing the nonlinear Constraints functions(both Equality and Inequality) of the problem.
ub :Ī vector of doubles, containing the upper bounds of the variables of size (1 X n) or (n X 1) where 'n' is the number of variables. lb :Ī vector of doubles, containing the lower bounds of the variables of size (1 X n) or (n X 1) where 'n' is the number of variables. beq :Ī vector of double, vector of doubles, related to 'Aeq' and represents the linear coefficients in the equality constraints of size (m1 X 1). Aeq :Ī matrix of doubles, containing the coefficients of linear equality constraints of size (m1 X n) where 'm1' is the number of linear equality constraints. b :Ī vector of doubles, related to 'A' and represents the linear coefficients in the linear inequality constraints of size (m X 1). A :Ī matrix of doubles, containing the coefficients of linear inequality constraints of size (m X n) where 'm' is the number of linear inequality constraints. x0 :Ī vector of doubles, containing the starting values of variables of size (1 X n) or (n X 1) where 'n' is the number of variables. A function, representing the objective function of the problem.
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