Multi-objective optimization using Fuzzy Evolutionary Strategies Optimization

[1]  Hans-Paul Schwefel,et al.  Evolution strategies – A comprehensive introduction , 2002, Natural Computing.

[2]  Wei Liu,et al.  A hybrid model using supporting vector machine and multi-objective genetic algorithm for processing parameters optimization in micro-EDM , 2010 .

[3]  Angelos P. Markopoulos,et al.  Artificial neural network models for the prediction of surface roughness in electrical discharge machining , 2008, J. Intell. Manuf..

[4]  Ivan Stojmenovic,et al.  A hybrid channel assignment approach using an efficient evolutionary strategy in wireless mobile networks , 2005, IEEE Transactions on Vehicular Technology.

[5]  R. Vinayagamoorthy,et al.  Parametric Optimization on Multi-Objective Precision Turning Using Grey Relational Analysis , 2014 .

[6]  A Pandey,et al.  Current research trends in variants of Electrical Discharge Machining: A review , 2010 .

[7]  P. Koumoutsakos,et al.  Evolution strategies for parameter optimization in flow control. , 1998 .

[8]  Rajkumar Roy,et al.  Evolutionary computing in manufacturing industry: an overview of recent applications , 2005, Appl. Soft Comput..

[9]  P.Narender Singh,et al.  Optimization by Grey relational analysis of EDM parameters on machining Al–10%SiCP composites , 2004 .

[10]  Amr M. Sauber,et al.  Multi-objective GA rule extraction in a parallel framework , 2011 .

[11]  S. Saha,et al.  Multi-objective optimization of the dry electric discharge machining process , 2009, 0908.0389.

[12]  Ms. Shruti Mehta,et al.  A Review on Current Research Trends in Die-Sinking Electrical Discharge Machining of Conductive Ceramics , 2009 .

[13]  Jerzy Balicki.  An adaptive quantum-based multiobjective evolutionary algorithm for efficient task assignment in distributed systems , 2009 .