Parallel CUDA implementation of the desirability-based scalarization approach for multi-objective optimization problems
Student Workshop on Bioinspired Optimization Methods and their Applications, BIOMA 2014, Ljubljana, Slovenya, 13 Eylül 2014, ss.93-104, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Basıldığı Şehir: Ljubljana
- Basıldığı Ülke: Slovenya
- Sayfa Sayıları: ss.93-104
- Anahtar Kelimeler: Aggre gation, CUDA, Desirability functions, Genetic algorithm, GPGPU programming, Multi-objective optimization, Parallelization, Scalarization
- TED Üniversitesi Adresli: Hayır
Özet
In this study, we present the results obtained for the parallel CUDA implementation of the previously proposed desirability-based scalarization approach for the solution of the multi-objective optimization problems. Our simulations show that compared to the sequential Java implementation, it is possible to find the same solutions (up to 16-time faster manner) by parallel CUDA implementation. We also try to outline our experiences of troubleshooting throughout the implementation as guidelines for upcoming researchers working in the same field.