Using genetic algorithm for dynamic and multiple criteria web-site optimizations
Document Type
Article
Publication Date
2-1-2007
Abstract
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. © 2005 Elsevier B.V. All rights reserved.
Recommended Citation
Asllani, Arben and Lari, Alireza, "Using genetic algorithm for dynamic and multiple criteria web-site optimizations" (2007). College of Business and Economics. 332.
https://digitalcommons.uncfsu.edu/college_business_economics/332