Use of IAs based approach for the Cooperative Periodic Market Problems

This study investigates the two traders’ periodic marketing problem in which both the spatial (where) and temporal (when) dimensions are to be decided simultaneously so as to maximize the total payoff during trading based on the itinerary. In literature, the periodic marketing problems are studied very few for the past decade, usually using the sequential strategy approaches. However, the solution by using sequential strategy tends to find the local optimal solution but not the global optimal solution. The difficulties encountered in the problem include: the spatial behavior of the individual consumers is uncertain, customers may from other neighboring sites based on the distance, the demand of a product is needed based on a specific time period (cycle), not all the market places need to be stayed and the same market place can be visited more than once. In this paper, an immune algorithm is used for solving such nonlinear periodic marketing problem. Numerical examples indicate that the proposed approach can efficiently and effectively search over promising solution regions to exhibit the superior performance of the proposed methodology for finding the optimal itinerant strategy during the specified planning horizon. Key-Words: Periodic marketing, Immune, Genetic algorithm, Sequential strategy