Improved Genetic Algorithms for correlative product combinatorial introduction model

Enterprises need to develop a process to determine how to find and develop new product ideas and finally, how to successfully introduce them to the marketplace. In the electronic commerce environment, many products are sold at the same marketplace, and we must consider the correlativity of products. Every product in the marketplace has substitutes and complements. To address this problem, conceptions of optimal Introduction period and correlative profit are presented. Based on the quantitative description of product life cycle, a non-linear semi-infinite programming model of new product introduction is proposed. The new model is solved through improved genetic algorithms. Optimal solution of the given example under several special conditions shows that this model is effective for enterprises.