Immune Algorithm with Searching Diversity and its Application to Resource Allocation Problem

Abstract

Immune system has powerful abilities such as memory, recognition and learning to respond to invaded antigens, and is expected to be applied to many industrial applications as well as neural networks. This paper proposes an algorithm imitating the immune system that is based on the somatic theory and the network hypothesis in order to make a plan for manufacturing systems. The former theory illustrates that somatic recombination and mutation contributes to increasing of the diversity of antibody. The others illustrates that mutual recognition network among the antibodies contributes to control of proliferation of clones.
This paper shows that the proposed algorithm based on these theories is capable of searching for a global solution not but local solutions through a resource allocation problem.