Software request and terms of use

A demo along with the main MVMO-SH script and several examples on how MVMO-SH can be used is offered for download free of charge through this web. Copyright restrictions apply. The original or modified versions of MVMO-SH may not be transferred to any third party without prior written consent of the proprietor. MVMO-SH is distributed in the hope that it will serve as a useful optimization tool for researchers and educators worldwide. Please note that the software and the associated literature come with no warranty whatsoever. The use of MVMO-SH in any publication must be duly acknowledged. Limited support can be obtained by contacting Prof. István Erlich (istvan.erlich@uni-due.de) or Dr. José L. Rueda (jose.rueda@uni-duisburg-essen.de).

Download

After filling and submitting the MVMO-SH request form, a password for downloading the encrypted .zip file containing the demo will be sent to you via email. To use MVMO-SH you will need MATLAB® version 7.9.0.529 or later.

Download the .zip file (last update: July 16, 2013) here. In order to properly decompress it, you may need 7-Zip.

Running an example

The demo is intended to demonstrate the features of the MVMO-SH in an intuitive manner. Based on several unconstrained minimization problems defined through standard benchmark optimization functions, the user can obtain insight into the underlying search process of MVMO-SH.

To run the demo, just type MVMOSH_demo at the Matlab prompt. Then, the GUI of MVMO-SH will pop up enabling the user to select a benchmark function (e.g. Schwefel’s function) as well as to modify the MVMO-SH settings. For instance, the problem dimension can be set between 2 and 30. If a high dimensional problem is defined, more than one particle would be preferable to initiate the search process. By default, for two dimensional problems, once the optimization has started, the evolution of the objective function, and the transformation function h and shape factors (corresponding to the global best particle for multi-particle search) throughout the optimization process, are displayed in interactive figures while results are printed in the MATLAB command window. The interactive visualization is not available for three or higher dimensional problems, but the optimization progress is printed in the MATLAB command window.