| As a new simulated evolutionary algorithm, the ant colony algorithm has been widely used for solving combinatorial problems, such as TSP, Quadratic Assignment problem, Arms-target allocation problem, assignment problem, frequency distribution, power system fault diagnosis and other NP-problems. Using the ACA to solve the problem of the combinatorial stock investment optimization, is still an emerging research, and has practical significance.Chaptersâ…¡toâ…¤are the core content of this paper. Chapterâ…¡describes the basic concepts and theory of the ACA, especially the generation and implementation process of the artificial ant colony algorithm, ACA model and the current research work. Chapterâ…¢focuses on the research methods of the securities investment, and describes it respectively in three aspects, i.e. the fundamental analysis, technical analysis and portfolio analysis. In chapterâ…£is the core content of this article, by analysis of the nature of the search process in the ACA, we simulate the behavior of investors, improve the algorithm appropriately, and establish the model. Finally, the method is tested and the expected results are obtained. In Chapterâ…¤, we compare the ACA with Simulated annealing algorithm, and the result reflects the superiority of the ant colony algorithm. The innovations of this paper is not only using the ACA to solving the combinatorial optimization problems just as other applications, but dig out the characteristics and advantages of the algorithm, simulate the behavior of investors and obtain our expected results.Ant colony algorithm is such a young and potential heuristic algorithm, and plays a significant role in solving a big class of combinatorial optimization problems in the computer science field. Furthermore, Portfolio Investment problem is an optimization problem with important theoretical and practical meaning. Thus, the research of the ant colony algorithm for Securities Investment problem has an important meaning. |
PDF Full Text Request