Web Page Interface Optimization Based on Nature-Inspired Algorithms

Abstract

This article describes how the conversion rate of a web page depends on the interface usability degree. Optimization of existing interfaces as the matter of improving their usability faces a number of difficulties. In the first place, the unified objective function selection method for such optimization is not set up; that is resulting in necessity of qualified experts' participation for its implementation. In the second place, the corresponding optimization problem will have a high dimension, which makes the classical optimization methods unsuitable for the problem solution. Nature-inspired algorithms have undeniable advantages in comparison with classical optimization algorithms for solving high-dimensional problems, such as for example the optimization of web interfaces by their usability criterion. In this article, new web page interface optimization methods based on nature-inspired algorithms are proposed. In particular, genetic algorithms (GAs), artificial bee colony algorithms (ABC), and charged system search algorithms (CSSs) were analyzed. The conducted experiments revealed the advantages of these algorithms for posed problem solutions and showed research prospects in this direction.