Pricing Process in Industrial Clusters Using Genetic Algorithm

Abstract

It’s more than one decade that industrial development based on the structure of industrial clusters as a new strategy has been used in the planning and policy by developing industrialized countries. Considering the importance of the role of industrial clusters in economic development programs, providing solutions to improve, progress and development of clusters has always been a concern for researchers and specialists.

The aim of this study is to provide a mechanism for pricing process of the product in this industrial-economic phenomenon; So that the structure of the proposed model is defined based on mechanisms and activities of the components of industrial clusters. The proposed pricing process is presented based on the concept of Stackelberg game theory and tariff pricing strategy, and in order to solve the model in production level of cluster, the meta-heuristic genetic algorithm is used. Finally, the performance and efficiency of the proposed model is studied in the form of a numerical example, and using the parameter tuning Taguchi method the optimal value of the model variables are presented. Based on the obtained results, the optimal wholesale price of cluster’s products are determined and each manufacturer select the appropriate tariff based on its optimal demand.

Keywords: Industrial Cluster, Tariff Pricing, Stackelberg Game, Genetic Algorithm, Taguchi Method