Cultural algorithm (CA) is an evolutionary optimization algorithm inspired from the principles of human social evolution. The overall framework of CA is modeled based on the biocultural evolution, in which genes and culture are two interacting forms of inheritance. CA consists of the belief and population spaces. As a cultural inheritance mechanism, the belief space shares the cultural information among the individuals of the population space to accelerate the evolution speed of the individuals by making use of the domain knowledge obtained from generation to generation. In this chapter, the capabilities of CA for structural optimization are further investigated and an improved CA (ICA) method is proposed for simultaneous size and shape optimization of dome-shaped structures. In the proposed ICA method, a new influence function is proposed to update the position of individuals in the search space. In addition, a dynamic stochastic mechanism is introduced by using a truncated geometric distribution to simulate the number of dimension changes in each individual. To investigate the effectiveness of the proposed ICA approach as well as different variants of the standard CA method, two size and shape optimization problems of lamella dome structures under stress, displacement, and frequency constraints are investigated.