Clustering-Based Analysis of Large-Scale Multiobjective Evolutionary  Algorithm Solution Sets

Majoju Sridhar Kumar,Dr. Gajendra Sharma

Clustering-Based Analysis of Large-Scale Multiobjective Evolutionary Algorithm Solution Sets

Authors

Majoju Sridhar Kumar,Dr. Gajendra Sharma

Keywords:

Multiobjective Optimization, Evolutionary Algorithms, Pareto Front, Clustering Techniques, Solution Selection, Large-Scale Optimization

Abstract

Multiobjective evolutionary algorithms (MOEAs) are broadly applied to the fieldof complex optimization problems that comprise a number of conflicting objectives. Thesealgorithms produce a huge quantity of nondominated solutions, which create an approximation of the Pareto front. This, however, causes increased complexities when itcomes to interpretation

References

Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), 182–197.

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Published

2024-09-20

How to Cite

Majoju Sridhar Kumar,Dr. Gajendra Sharma. (2024). Clustering-Based Analysis of Large-Scale Multiobjective Evolutionary Algorithm Solution Sets . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 2808–2814. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4482