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Solver Termination Messages

The SQP solver terminates with one of the following messages:

Converged

The SQP solver has found a local minimum within the convergence tolerance specified.

Maximum number of iterations reached

The SQP solver has reached the limit on the maximum number of iterations, but has not satisfied the convergence criteria.

Maximum specified time reached

The SQP solver has spent more time than the prespecified maximum real time for the optimization process, but has not satisfied the convergence criteria.

Line search cannot improve further

The SQP solver cannot make any progress in the line search. One possibility is that a solution has been found, but the convergence tolerance is set too small.

Out of memory

The NLP problem is too large for the SQP solver to solve. This could be due to a limitation in the memory allocated to the procedure.

Objective function cannot be evaluated at starting point

The objective function cannot be evaluated at the starting point.

At least one constraint cannot be evaluated at starting point

At least one of the constraints cannot be evaluated at the starting point.

Gradient of objective function cannot be evaluated at starting point

The gradient of the objective function cannot be evaluated at the starting point.

Gradient of at least one constraint cannot be evaluated at starting point

The gradient of at least one of the constraints cannot be evaluated at the starting point.

Did not converge

The NLP problem has not been solved. There could be several reasons why this happens. For instance, maybe a QP subproblem could not be solved within a preset number of iterations.

Second order optimality is not satisfied

SQP has located a point satisfying the first-order condition but not the second-order condition.

Problem may be unbounded

SQP has located a feasible point, but its objective function value is extremely low. SQP can improve the objective function even further as well.

Problem may be infeasible

SQP cannot locate a feasible point.

Problem is infeasible

SQP has identified an infeasibility in the problem.

Problem solved by the OPTMODEL presolver

The problem was solved by the OPTMODEL presolver.