Multi-criteria website optimization using novel quantum inspired tri-objective ACO based approach

摘要

The phenomenal growth and ever increasing popularity of the e-commerce has revolutionized our way of shopping. Observing this lucrative opportunity, every organization is competing for attracting new customers, while retaining the existing ones for the increased transactions on their e-commerce website. To achieve these goals, the organizations require providing an effective and efficient website to their customers. In order to provide such website, the adaptation mechanism is used to update the website structure considering several criteria. These criteria include maximizing the sell or transaction, maximizing the visualization while minimizing the download time, among others. Addressing such multiple criteria for the simultaneous optimization for improved website structure makes it a typical multi-criteria combinatorial optimization problem. In recent years metaheuristic based techniques have gained a lot of popularity to solve such optimization problems. In this paper a novel tri-criteria quantum inspired ant colony optimization metaheuristic is discussed to address the tri-criteria website optimization. The proposed tri-criteria quantum inspired ACO has adopted the concept of Q-bit representation and Q-gate from quantum inspired evolutionary algorithm for pheromone representation and update explained in quantum ant colony optimization.