An immune co-evolutionary algorithm for n-th agent's traveling salesman problem

The purpose of this paper is to evaluate an immune optimization algorithm using a biological immune co-evolutionary phenomenon and cell-cooperation. The co-evolutionary model searches solutions through the interactions between two kinds of agents, on the agent is called immune agent, which optimizes the cost of its own work. The other is call antigen agent, which realized the equal work assignment. This algorithm solves the division-of-labor problems in multi-agent system (MAS) through the three kinds of interactions: division-and-integration processing is used for optimization of the work-cost of immune agents and immune cell-cooperation is used to perform equal work assignment as a result of evolving the antigen agents. To investigate the validity, this algorithm is applied to "n-th agent's traveling salesman problem" as a typical problem of MAS. The good property on solving for MAS will be clarified by some simulations.