ev-MOGA Multiobjective Evolutionary Algorithm 1.0

ev-MOGA Multiobjective Evolutionary Algorithm has been developed by the Predictive Control and Heuristic optimization Group at Universitat Politdoducnica de Valdoduncia. 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. MartdoTsnez, J.M. Herrero, J. Sanchis, X. Blasco and S. GarcdoTsa-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. MartdoTsnez, 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. MartdoTsnez, 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. MartdoTsnez, 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. GarcdoTsa-Nieto, X. Blasco, V. Romero-GarcdoTsa, J. V. SdodAnchez-PdoTerez 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. DisedoT-o Multiobjetivo de controladores PID para el Benchmark de Control 2008-2009. Revista Iberoamericana de AutomdodAtica e InformdodAtica Industrial. Vol. 6, Num. 4, pp. 93 - 103 , 2009. (ISSN: 1697-7912)Basic instructionsThe d-deDUev-MOGAdescription.pdfd-deDt 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 d-deDUrun_evMOGA.md-deDt. which contains the parameter configuration of the ev-MOGA and defines the optimization problem to solve.3) Execute the script d-deDUrun_evMOGA .md-deDt to run the ev-MOGA. After execution, variables ParetoFront and ParetoSet variables are obtained in the workspace

Requirements:	No special requirements
Platforms:	Matlab
Keyword:	Autom Tica,  Benchmark,  Controladores,  Dise,  Evmogadescriptionpdf,  Iberoamericana,  Inform Tica,  Multiobjetivo,  Revista
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