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, Slovenia, 13 September 2014, pp.93-104, (Full Text)
- Publication Type: Conference Paper / Full Text
- City: Ljubljana
- Country: Slovenia
- Page Numbers: pp.93-104
- Keywords: Aggre gation, CUDA, Desirability functions, Genetic algorithm, GPGPU programming, Multi-objective optimization, Parallelization, Scalarization
- TED University Affiliated: No
Abstract
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.