International Journal of Optimization in Civil Engineering
دانشگاه علم و صنعت ایران
Iran University of Science & Technology
http://ijoce.iust.ac.ir
18
agent2
2228-7558
en
jalali
1390
9
1
gregorian
2011
12
1
1
4
online
1
fulltext
en
OPTIMAL SHAPE DESIGN OF GRAVITY DAMS BASED ON A HYBRID META-HERURISTIC METHOD AND WEIGHTED LEAST SQUARES SUPPORT VECTOR MACHINE
Optimal design
Optimal design
پژوهشي
Research
<font size="2">A hybrid meta-heuristic optimization method is introduced to efficiently find the optimal shape of concrete gravity dams including dam-water-foundation rock interaction subjected to earthquake loading. The hybrid meta-heuristic optimization method is based on a hybrid of gravitational search algorithm (GSA) and particle swarm optimization (PSO), which is called GSA-PSO. The operation of GSA-PSO includes three phases. In the first phase, a preliminary optimization is accomplished using GSA as local search. In the second phase, an optimal initial swarm is produced using the optimum result of GSA. Finally, PSO is employed to find the optimum design using the optimal initial swarm. In order to reduce the computational cost of dam analysis subject to earthquake loading, weighted least squares support vector machine (WLS-SVM) is employed to accurately predict dynamic responses of gravity dams. Numerical results demonstrate the high performance of the hybrid meta-heuristic optimization for optimal shape design of concrete gravity dams. The solutions obtained by GSA-PSO are compared with those of GSA and PSO. It is revealed that GSA-PSO converges to a superior solution compared to GSA and PSO, and has a lower computation cost. </font>
Concrete gravity dams; optimal shape; gravitational search algorithm; particle swarm optimization; weighted least squares support vector machine
609
632
http://ijoce.iust.ac.ir/browse.php?a_code=A-10-1-41&slc_lang=en&sid=1
J.
Salajegheh
`18003194753284600328`

18003194753284600328
Yes
S.
Khosravi
`18003194753284600329`

18003194753284600329
No