Using genetic algorithm for dynamic and multiple criteria web-site optimizations

In today’s competitive electronic marketplace, companies try to create long-lasting relations with their online customers. Log files and registration forms generate millions of online transactions. Companies use new techniques to “mine” these data and establish optimal online storefronts to maximize their web presence. Several criteria, such as minimization of download time, maximization of web-site visualization and product association level, can be used for the optimization of virtual storefronts. This paper introduces a genetic algorithm, to be used in a model-driven decision-support system for web-site optimizations. The algorithm ensures multiple criteria web-site optimizations, and the genetic search provides dynamic and timely solutions independent of the number of objects to be arranged.