Title :
Particle Gradient Multi-objective Evolutionary Algorithm Based on GPU with CUDA
Author :
Yue, Xuezhi ; Wu, Zhijian ; Li, Kangshun
Author_Institution :
State Key Lab. of Software Eng., Wuhan Univ., Wuhan, China
Abstract :
In the paper, particle gradient multi-objective evolutionary algorithm (PGMOEA) on GPU is presented. PGMOEA extends the classical particle dynamic multi-objective evolutionary algorithm by incorporating the gradient information of each particle from evolutionary programming. We perform experiments to compare PGMOEA on GPU with PGMOEA on CPU and demonstrate that PGMOEA on GPU is much more effective and efficient than PGMOEA on CPU.
Keywords :
computer graphic equipment; coprocessors; evolutionary computation; gradient methods; parallel architectures; CUDA; GPU; compute unified device architecture; evolutionary programming; particle dynamic multiobjective evolutionary algorithm; particle gradient multiobjective evolutionary algorithm; Arrays; Computational modeling; Evolutionary computation; Graphics processing unit; Instruction sets; Optimization; Programming; computeunifieddevice architecture; graphics processingunit; multi-objective optimization problem; particle gradient multi-objective evolutionary algorithm;
Conference_Titel :
Information Science and Engineering (ISISE), 2010 International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-428-2
DOI :
10.1109/ISISE.2010.136
