The NEOS Server offers filter for the solution of nonlinearly-constrained optimization problems. Problems can be submitted to filter on the NEOS server in AMPL format.
filter implements a Sequential Quadratic Programming solver that is suitable for large nonlinearly-constrained problems with a modest number of degrees of freedom. filter implements a sequential quadratic programming (SQP) trust-region algorithm with a "filter" to promote global convergence. The filter is a list of pairs of objective values and norms of constraint violations. A new step is accepted whenever it improves the objective or the constraints compared to the filter. Otherwise, the step is rejected.
filter was developed by Roger Fletcher and Sven Leyffer. Additional information on filter can be found in the User Manual for filterSQP.
The user must submit a model in AMPL format. Examples are provided in the examples section of the AMPL website.
The problem must be specified in a model file. A data file and commands files may also be provided. If the commands file is specified, it must contain the AMPL solve command; however, it must not contain the model or data commands. The model and data files are renamed internally by NEOS. The commands file may include option settings for the solver. To specify solver options, add
solve
model
data
option filter_options 'OPTIONS';