Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/78420
Title: An ensemble approach to multi-objective evolutionary algorithm
Authors: Pratama, Januar Ananta Dinar
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2019
Abstract: Multi-objective optimization refers to the procedure of obtaining a set of feasible solution for multiple objective functions. Based on the no free lunch (NFL) theorem, an optimization technique would never exceed all other optimization techniques on every type of optimization problem. Ensemble approach is one method to improve the performance of the multi-objective algorithm. This method is combining two or more multi-objective algorithms to get the benefit of each individual algorithm. An ensemble of multi-objective optimization with three multi-objective optimization algorithms (MOEA/D, NSGA-III, SMODE) has been implemented on the multi-objective benchmark test function (a set of many and multi-objective bound constrained benchmark problems). The ensemble method has the best performance in comparison to its former individual algorithm. The results of the simulation show the ensemble has better Pareto-optimal front based on the convergence, diversity and quantitative performance.
URI: http://hdl.handle.net/10356/78420
Schools: School of Electrical and Electronic Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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