ev-MOGA Multiobjective Evolutionary Algorithm (Scripts) Publisher's description
from Juan M. Herrero
ev-MOGA Multiobjective Evolutionary Algorithm has been developed by the Predictive Control and Heuristic optimization Group at Universitat PolitГЁcnica de ValГЁncia
ev-MOGA Multiobjective Evolutionary Algorithm has been developed by the Predictive Control and Heuristic optimization Group at Universitat PolitГЁcnica de ValГЁncia. ev-MOGA is an elitist multi-objective evolutionary algorithm based on the concept of epsilon dominance. ev-MOGA, tries to obtain a good approximation to the Pareto Front in a smart distributed manner with limited memory resources. It also adjusts the limits of the Pareto front dynamically.
Details about ev-MOGA are described in (please, cite this algorithm as):
 M. MartГnez, J.M. Herrero, J. Sanchis, X. Blasco and S. GarcГa-Nieto. Applied Pareto multi-objective optimization by stochastic solvers. Engineering Applications of Artificial Intelligence. Vol. 22 pp. 455 - 465, 2009 (ISSN:0952-1976).
The algorithm is also described in:
 J.M. Herrero, M. MartГnez, J. Sanchis and X. Blasco. Well-Distributed Pareto Front by Using the epsilon-MOGA Evolutionary Algorithm. Lecture Notes in Computer Science, 4507, pp. 292-299, 2007. Springer-Verlag. (ISSN: 0302-9743)
ev-MOGA has been used in:
 J.M. Herrero, X. Blasco, M. MartГnez, C. Ramos and J. Sanchis. Robust Identification of a Greenhouse Model using Multi-objective Evolutionary Algorithms. Biosystems Engineering. Vol. 98, Num. 3, pp. 335 - 346, Nov 2007. (ISSN 1537-5110)
 J.M. Herrero, X. Blasco , M. MartГnez, J. Sanchis. Multiobjective Tuning of Robust PID Controllers Using Evolutionary Algorithms. Lecture Notes in Computer Science, 4974, pp. 515 - 524, 2008. Springer-Verlag. (ISSN: 0302-9743)
 J. M. Herrero, S. GarcГa-Nieto, X. Blasco, V. Romero-GarcГa, J. V. SГЎnchez-PГ©rez and L. M. Garcia-Raffi. Optimization of sonic crystal attenuation properties by ev-MOGA multiobjective evolutionary algorithm. Structural and Multidisciplinary Optimization. Vol. 39, num. 2, pp. 203 - 215, 2009 (ISSN:1615-1488).
 G. Reynoso, X. Blasco, J. Sanchis. DiseГ±o Multiobjetivo de controladores PID para el Benchmark de Control 2008-2009. Revista Iberoamericana de AutomГЎtica e InformГЎtica Industrial. Vol. 6, Num. 4, pp. 93 - 103 , 2009. (ISSN: 1697-7912)
The вЂњev-MOGAdescription.pdfвЂќ file contains the description of the ev-MOGA algorithm. You should read it before using the algorithm in order to understand how it works. Two multiobjective problems mop1.m and mop4.m are included as examples.
1) Create the Matlab function used to evaluate the objective functions (e.g. mop1.m)
2) Modify вЂњrun_evMOGA.mвЂќ. which contains the parameter configuration of the ev-MOGA and defines the optimization problem to solve.
3) Execute the script вЂњrun_evMOGA .mвЂќ to run the ev-MOGA. After execution, variables ParetoFront and ParetoSet variables are obtained in the workspace
System Requirements:MATLAB 7.1.0 (R14SP3)
Program Release Status: New Release
Program Install Support: Install and Uninstall