Geology Reference
In-Depth Information
Chapter 12
Optimum Design of Structures
for Earthquake Loading by a
Cellular Evolutionary Algorithm
and Neural Networks
Saeed Gholizadeh
Urmia University, Iran
ABSTRACT
The present chapter deals with optimum design of structures for earthquake induced loads by taking
into account nonlinear time history structural response. As the structural seismic optimization is a time
consuming and computationally intensive task, in this chapter, a methodology is proposed to reduce the
computational burden. The proposed methodology consists of an efficient optimization algorithm and a
hybrid neural network system to effectively predict the nonlinear time history responses of structures.
The employed optimization algorithm is a modified cellular genetic algorithm which reduces the required
generation numbers compared with the standard genetic algorithm. Also, the hybrid neural network
system is a combination of probabilistic and generalized regression neural networks. Numerical results
demonstrate the computational merits of the proposed methodology for seismic design optimization of
structures.
INTRODUCTION
been solved using gradient-based algorithms. As
the mathematical programming based methods
need gradient calculations, the considerable part
of the optimization process is devoted to the sen-
sitivity analysis and the computational work of
these methods is usually high. Optimal design of
real-world structures subject to seismic loading is
Optimum design of structures is a process of
selecting the design variables such that an ob-
jective function is minimized while all of the
design constraints are satisfied. During the last
decades, structural optimization problems have
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