期刊
SWARM AND EVOLUTIONARY COMPUTATION
卷 35, 期 -, 页码 1-13出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.swevo.2016.08.004
关键词
Topology optimization; Structure representation; Crossover; Mutation; GPU computing; Evolutionary algorithm
资金
- SERB, Department of Science and Technology (DST), India [SB/FTP/ETA-28/2013]
- IIT Guwahati [SG/ME/DS/P/01]
- NVIDIA Corporation
Although structural topology optimization, as a discrete optimization problem, has been successfully solved several times in the literature using evolutionary algorithms (EAs), the two key difficulties lie in generating geometrically feasible structures and handling a high computation time. These two challenges are addressed in this paper by adopting triangular representation for two-dimensional continuum structures, related crossover and mutation operators, and by performing computations in parallel on the graphics processing unit (GPU). Two case studies are solved on the GPU that show 5 x of speedup over CPU implementation. The parametric study on the population size of EA shows that the approximate Pareto-optimal solutions can be evolved using a small population with the proposed EA operators. (C) 2016 Elsevier B.V. All rights reserved.
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