Applying Evolutionary Clustering Technique for finding the most Significant Solution from the Large Result Set obtained in Multi-Objective Evolutionary Algorithms
نویسندگان
چکیده
Multicriteria optimization applications can be implemented using Pareto optimization techniques including evolutionary Multicriteria optimization algorithms. Many real world applications involve multiple objective functions and the Pareto front may contain a very large number of points. Choosing a solution from such a large set is potentially intractable for a decision maker. Previous approaches to this problem aimed to find a representative subset of the solution set.
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