05805397

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05805397 Sharma, Deepak Collet, Pierre GPGPU-compatible archive based stochastic ranking evolutionary algorithm (G-ASREA) for multi-objective optimization. Schaefer, Robert (ed.) et al., Parallel problem solving from nature -- PPSN XI. 11th international conference, Krak\'ow, Poland, September 11--15, 2010. Proceedings, Part II. Berlin: Springer (ISBN 978-3-642-15870-4/pbk). Lecture Notes in Computer Science 6239, 111-120 (2010). 2010 Berlin: Springer EN

doi:10.1007/978-3-642-15871-1_12

Summary: In this paper, a GPGPU (general purpose graphics processing unit) compatible Archived based Stochastic Ranking Evolutionary Algorithm (G-ASREA) is proposed, that ranks the population with respect to an archive of non-dominated solutions. It reduces the complexity of the deterministic ranking operator from $O(mn ^{2})$ to $O(man)$ and further speeds up ranking on GPU. Experiments compare G-ASREA with a CPU version of ASREA and NSGA-II on ZDT test functions for a wide range of population sizes. The results confirm the gain in ranking complexity by showing that on 10K individuals, G-ASREA ranking is $\approx \times 5000$ faster than NSGA-II and $\approx \times 15$ faster than ASREA.