New Hybrid Evolutionary Algorithm for Solving Multi-Objective Optimization Problems
published by Aِl-Baath University
in 2017
in
and research's language is
العربية
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Abstract in English
Multi-objective evolutionary algorithms are used in a wide range
of fields to solve the issues of optimization, which require several
conflicting objectives to be considered together. Basic evolutionary
algorithm algorithms have several drawbacks, such as lack of a
good criterion for termination, and lack of evidence of good
convergence. A multi-objective hybrid evolutionary algorithm is
often used to overcome these defects.
References used
A. Abraham, L. Jain, and R. Gldenberg,2004. Evolutionary Multi- Objective optimization- theorical Advances and Applications, 1st ed
Coello Coello-C.A., Van Veldhuizen-D.A., Lamont-G.B.,2007. Evolutionary Algorithms for Solving Multi-Objective Problems, Springer
G. Ashish and S. Dehuri,2004. Evolutionary Algorithms for Multi- Criterion Optimization A Survey, International Journal of Computing and Information Sciences, vol. 2