Multi-objective Differential Evolution Algorithm with Spherical Pruning based on preferences

A MOEA with spherical pruning based on preferences to approximate Pareto front

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IMPORTANT: This toolbox was developed as a part of my PhD (concluded 2014). I decided to keep
this version as it is for comparison purposes and it won't be updated.
I invite you to check the new eXtended version of this algorithm, that will be updated with new mechanisms and features, according to the progress of our research on the topic:
https://www.mathworks.com/matlabcentral/fileexchange/65145
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This code implements a version of the multi-objective differential evolution algorithm with spherical pruning based on preferences (spMODE-II, second version of the spMODE algorithm) described in:

Gilberto Reynoso-Meza. Controller Tuning by Means of Evolutionary Multiobjective Optimization: a Holistic Multiobjective Optimization Design Procedure. PhD. Thesis (2014), Universitat Politècnica de València. Url: http://hdl.handle.net/10251/38248. Supervisors: Javier Sanchis and Xavier Blasco.

&

Reynoso-Meza, G., Sanchis, J., Blasco, X., & García-Nieto, S. (2014). Physical programming for preference driven evolutionary multi-objective optimization. Applied Soft Computing, 24, 341-362.

It is a MOEA with mechanisms to improve and deal with:

-- Diversity
-- Pertinency
-- Many-objective optimization instances
-- Constrained optimization instances.

It uses:

-- Physical Programming, in order to incorporate designer's preferences.
-- Size control of the approximated Pareto front using the above information.
-- Spherical pruning, in order to improve spreading.