| By means of structural optimization, not only the weight of structures can be reduced, but also the strength, stiffness, vibration behavior, buckling stability, and other performances of structures can be improved efficiently. Structural optimization is an important research direction in the computational mechanics and modern design field.The research work in the dissertation consists of two major parts. The first part proposes several improved measures on GA based on the analysis of the GA's theory and recent research of GA according to special property and requirements of structural optimization problems. The second part describes application of improved GA in all types of structural optimization problems. The numerical test and algorithmic comparison show that improved measures on GA are feasible and efficient.The research work will be introduced as follows:In chapter 1, the research developments of GA are surveyed, which include the history of development and characteristic for GA, research of the theory, evaluation of constraint handling and fitness function value, conference and forum. In the following section, applications of GA are discussed, especially in structural optimization. Existent problems applied to structural optimization are pointed out. In the last section, the main contents of the research in this dissertation are presented.In chapter 2, the process and fundament of simple GA are introduced. The basic terms are presented firstly, which include the relationships of chromosome, gene, alleles, locus, genetype, phenotype between the biology and GA. Then the process and experiential parametric selections of GA are given. Finally schema theorem is described. Building block hypothesis shows that GA has ability of finding the global optimum solution. Implicit parallelism and convergence are analyzed.In chapter 3, improvements on GA are investigated. Surrogate constraint handling, surrogate reproduction, improvement on individuals in mating pool by complex method, competitive elitist model, investigation of coded mechanism and improvement on crossover operator for binary coding are proposed.The contents of the following four chapters show that the improvements in this dissertation are feasible and effective by all kinds of typical examples.In chapter 4, GA is applied to sizing optimization of truss with continuous and discrete variables. In sizing optimization of truss with continuous variables, solutions between GA and the traditional methods are compared, which reveals that satisfying solutions are achieved, and that improved GA are feasible and effective. Improved GA doesn't depend on choice of penalty factor, competitive elitist model can provide more opportunity to be inherited to offspring for excellent genes, and individual feasibility improved with complex method canaccelerate convergence. In sizing optimization of truss with discrete variables, integer coding is used and compared with binary coding. The numerical solutions show the integer-coded GA is effective. When number of the discrete value between representation for binary coding and in discrete list can't be corresponded by one-to-one, integer coding is predominant, and better solutions are achieved under the same parameters.In chapter 5, GA is applied to configuration optimization of truss with mixed variables and topology optimization of truss with singularity. In configuration optimization of truss with mixed variables, mixed coded strategies are proposed which are binary and floating coding, integer and floating coding. Comparing the numerical solutions of binary coding and mixed coding, better solutions are obtained with the mixed coding, and the numerical solutions in most examples with integer and floating coding are best. In topology optimization of truss with singularity, a new mathematic formula with the topological variables is proposed. The numerical examples prove that the global optimum can be gained. In addition, GA is applied to (0,1) programming topology optimization of truss, when the c...
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