Cultural Algorithm And Its Application In Architecture Creative Design

It has frequently been suggested that cultural evolution enables societies to evolve or adapt to their environments at rates that exceed that of biological evolution based upon genetic inheritance alone. In the process of population evolution, the experience of individuals and the exchange of knowledge in the population promote the evolution of population. Based on these thoughts, Reynolds proposed Cultural Algorithm (CA) in 1994, which attracts a lot of foreign researchers, but not our Chinese. Cultural Algorithm is a new computable framework of Evolution Algorithm derived from the cultural evolution process. CA has two major components, a population component and a belief component. The main idea of CA is individuals from the population component interact with knowledge in the belief space during the search process, individual experience can modify knowledge stored in the belief space and that knowledge can likewise be used to influence individuals in the population.Concept of CA is more easily understood, further more it can reflect evolution process of society accurately than other optimization algorithms. Traditional ECs have limited or implicit mechanisms for representing and storing individual's global acquired knowledge to be passed from generation to generation while Cultural Algorithm, which models the evolution of the culture component of an evolutionary computational system over time, is presented to provide an explicit mechanism for acquisition, storage and integration of individual and group's problem solving experience and behavior. Therefore, CA has been successfully applied to many areas, such as Dynamic Constraint Optimization Problems,Optimization Problems, Data Mining and Multi-objective problems. Systematic analysis and mathematical foundation has not formed since research on Cultural Algorithm has just begun. There are many problems still need to be studied further. Especially domestic scholars have failed to pay sufficient attention to CA. Therefore, it is necessary to carry out systematical and comprehensive study on the origin, principle, applications of CA. The paper is expected to attract more scholars'attention and to provide convenience for fellow-up scholars.The main research work is as follows:1. Elaborate on the principle, mechanisms, features and application of Cultural Algorithm, based on the systematic study of vast literature about Cultural Algorithm.2. Bring forward a Cultural Genetic Algorithm based on Schema Fetching (CGASF). This algorithm embeds GA into the cultural algorithm framework; compose an algorithm with GA main population space and belief space. The worst individuals of the main population space are organized periodically to study the optimal schema that the belief space provides. In this way, it exploits the information sufficiently that the optimum individual carries and speeds up the evolutionary process.3. Bring forward a Particle Swarm Optimization based on Cultural Algorithm for solving constrained optimization problems. This algorithm employs PSO which uses Gaussian and Cauchy probability distributions in population space, and uses situational knowledge and normative knowledge in belief space to guide the evolution of the population. Experiments results show that this method can exploit the information that the optimum individual carries sufficiently and speeds up the evolutionary process.4. Apply Cultural Algorithm based on schema learning into architecture creative design. Experiment results show that this method can produce creative architecture products that satisfy user's demand more quickly, and need less labor during the evolutionary process. By applying Cultural Algorithm into architecture creative design, we not only exploit a new application area for Cultural Algorithm, but also provide a new method for architecture creative design.