Bilevel parallel genetic algorithms for optimization of large steel structures

被引:142
作者
Sarma, KC
Adeli, H [1 ]
机构
[1] Qwest Commun Int Inc, Dublin, OH 43016 USA
[2] Ohio State Univ, Dept Civil & Environm Engn & Geodet Sci, Columbus, OH 43210 USA
关键词
D O I
10.1111/0885-9507.00234
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This article is concerned with optimization of very large steel structures subjected to the actual constraints of the American Institute of Steel Construction ASD and LRFD specifications on high-performance multiprocessor machines using biologically inspired genetic algorithms. First, parallel fuzzy genetic algorithms (GAs) are presented for optimization of steel structures using a distributed memory Message Passing Interface (MPI) with two different schemes: the processor farming scheme and the migration scheme. Next, two bilevel parallel GAs are presented for large-scale structural optimization through judicious combination of shared memory data parallel processing using the OpenMP Application Programming Interface (API) and distributed memory message passing parallel processing using MPI. Speedup results are presented for parallel algorithms.
引用
收藏
页码:295 / 304
页数:10
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