تقرير
The Cone epsilon-Dominance: An Approach for Evolutionary Multiobjective Optimization
| العنوان: | The Cone epsilon-Dominance: An Approach for Evolutionary Multiobjective Optimization |
|---|---|
| المؤلفون: | Batista, Lucas S., Campelo, Felipe, Guimarães, Frederico G., Ramírez, Jaime A. |
| سنة النشر: | 2020 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Neural and Evolutionary Computing, I.2.8 |
| الوصف: | We propose the cone epsilon-dominance approach to improve convergence and diversity in multiobjective evolutionary algorithms (MOEAs). A cone-eps-MOEA is presented and compared with MOEAs based on the standard Pareto relation (NSGA-II, NSGA-II*, SPEA2, and a clustered NSGA-II) and on the epsilon-dominance (eps-MOEA). The comparison is performed both in terms of computational complexity and on four performance indicators selected to quantify the quality of the final results obtained by each algorithm: the convergence, diversity, hypervolume, and coverage of many sets metrics. Sixteen well-known benchmark problems are considered in the experimental section, including the ZDT and the DTLZ families. To evaluate the possible differences amongst the algorithms, a carefully designed experiment is performed for the four performance metrics. The results obtained suggest that the cone-eps-MOEA is capable of presenting an efficient and balanced performance over all the performance metrics considered. These results strongly support the conclusion that the cone-eps-MOEA is a competitive approach for obtaining an efficient balance between convergence and diversity to the Pareto front, and as such represents a useful tool for the solution of multiobjective optimization problems. Comment: 42 pages, 18 figures |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2008.04224 |
| رقم الأكسشن: | edsarx.2008.04224 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |