Using genetic algorithms bounded by dynamic linear constraints for marketing/production joint decision making

The prosperity of a firm depends highly on the functional integration of its various departments, and in particular the co-operation between the production and the marketing departments appears to have a large impact on the well-being of a firm. Due to the fact that the existence of both production and marketing decisions creates models which are already considerably complex, few of the models incorporate competition. In this paper we present how a genetic algorithm (GA) incorporated with some heuristic technique can be used for obtaining optimal or near optimal solutions for this kind of problem. The uniqueness of our approach lies in the concept of using the GA within a GA. Its performance is compared with the result presented by previous research. The results show that the genetic algorithm approach can be successfully used in the balance of production and promotion.