Ryo Kanai

Proposal and Evaluation of Improved Immune Algorithm

The Immune Algorithm (IA), which is optimum method based the human immune system, is suitable for gaining several solutions at once. This method is similar to Genetic Algorithms (GA), and is hoped to be able to use several local rules of GA. On the other hands, IA may have the demerit that is hard to deal with many parameters. In this paper, we suggest the improved Immune Algorithm. This method is improved by review of Immune System, and uses both secondary response and response control by endocrine system. Its hoped that new added functions affect searching ability. Additionally, the effect may be able to cut one of complex parameters. This method is applied to some simple problems that search the extremum in the functions and traveling salesman problem. As the results, its able to control one of parameters depending on the searching situation and suggested the potential of cutting parameter. The validity of this method is checked.

New Optimization Technique Using Microcosm and Its Applications

It is useful to propose a new algorithm to analyze the complicated optimization problems by imitating the functions of living things. In this study, it is object to propose new optimization method using the microcosm which is model of natural ecosystem. The microcosm in this paper is constituted by considering a bone forming ecosystem that the interaction of each cell is clear and able to be regarded as ecosystem. By combining the proposed microcosm and GA, the optimization problems are analyzed. The problems to search a minimum point in the multiple-peak function, and to search the plane structure of the minimum value subjected to a load are analyzed. Moreover, the validity of design solution is checked for the several design conditions.