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  • Last update: 5 years ago
  • Total downloads: 59
  • Operating system: Linux, Mac OS X, Win All, BSD, Solaris
  • Publisher: Juan M. Herrero
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scripts default iconev-MOGA Multiobjective Evolutionary Algorithm (Scripts) Publisher's description

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):

[1] 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:

[2] 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:

[3] 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)

[4] 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)

[5] 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).

[6] 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)
Basic instructions

The “ev-MOGAdescription.pdf” 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.

Basic instructions:
1) Create the Matlab function used to evaluate the objective functions (e.g. mop1.m)
2) Modify “run_evMOGA.m”. which contains the parameter configuration of the ev-MOGA and defines the optimization problem to solve.
3) Execute the script “run_evMOGA .m” 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

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