Genetic Algorithm And Its Applied Research In Structural Engineering Optimization

Genetic Algorithm (GA) is one of the main directions in today抯 compute science. Its application in structural optimization catches more and more attention. Some essential aspects about Genetic Algorithm and structural optimization are discussed in this paper. The basic structure of GA and its main characteristics are introduced. GA抯 algorithm structure design and arithmetic operators?designs are presented when GA applies on optimal design. In this paper, the characteristics of structural optimization and its actualities are introduced, and some ordinary algorithms are discussed, and some basic rules about GA抯 algorithm structure design and arithmetic operators? designs when its applies on structural optimization are proposed. Two kinds of algorithms, Two-phase Genetic Algorithm with Movable Boundaiy and Pareto Genetic Algorithm with Fuzzy Constraints, are discussed respectively to deal with single objective and multi-objective structural optimization. Also the examples prove those algorithms are effective and efficient. In the Two-phase GA with Movable Boundary, the whole algorithm is divided into two phases according the hierarchy optimal theory. The first phase is focused in explore and the second phase in exploit. Movable boundary technique makes this algorithm more robust. And in the Pareto GA, a group of nondozninated points instead of one optimal solution can be gained in a single process. The fuzzy theory is applied in order to treat with the constraints more efficient. The parallel models of Genetic Algorithm and the architecture of structural optimization software are discussed in the last part of this paper.