NEOS Interfaces to PSwarm

Sample Submissions
WWW Form - XML-RPC

PSwarm

The NEOS Server offers PSwarm v1.1 for the solution of bound and linear constrained optimization problems in AMPL format. PSwarm is a global optimization solver for bound and linear constrained problems (for which the derivatives of the objective function are unavailable, inaccurate or expensive). The algorithm combines pattern search and particle swarm. Basically, it applies a directional direct search in the poll step (coordinate search in the pure simple bounds case) and particle swarm in the search step. PSwarm makes no use of derivative information of the objective function. It has been shown to be efficient and robust for smooth and nonsmooth problems, both in serial and in parallel.

We expect that all publications describing work using this software quote the following reference:

For further information about PSwarm, contact aivaz@dps.uminho.pt.

The following is a list of options for PSwarm that the user may set via the AMPL input files. For example, option pswarm_options "size=60";


Using the NEOS Server for PSwarm/AMPL


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

  option pswarm_options 'OPTIONS';
where OPTIONS is a list of one or more of the available solver options for AMPL.

Web Submission Form
Model File
Enter the location of the ampl model (local file)
Data File
Enter the location of the ampl data file (local file)
Commands File
Enter the location of the ampl commands file (local file)
Comments
Additional Settings


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Please do not click the 'Submit to NEOS' button more than once.