Using immune-based genetic algorithms for single trader’s periodic marketing problem

This study considers a single trader’s periodic marketing problem in which both the spatial (where) and the temporal (when) dimensions are decided simultaneously to maximize the total payoff during the trading time horizon. In the past, researchers paid more attention on the periodic marketing problems to figure out why such markets arise and how they are organized in space. Few investigations have been carried out to find the most profitable itinerant route for the traders. In this paper, an immune-based genetic algorithm has been applied to transfer the mathematical model of the natural immune system into computational algorithm. Numerical examples indicate that the proposed approach can perform well for solving the single trader’s periodic marketing problem in terms of obtaining the most profitable itinerant strategies.