Optimizing Websites for Online Customers

The fast growth, along with the all encompassing presence, of the World Wide Web has given an unprecedented opportunity for organizations to maintain a strong online presence through a website catering to the requirements of varied users in an effective and efficient manner. In order to arrive at an optimal web site, relevant criteria need to be considered for selecting a set of web objects, from amongst a large number of web objects, which should be displayed on a web site. This being a combinatorial optimization problem would require simultaneous optimization of multiple relevant objectives based on relevant and key criteria for a given web site. In this paper, the multi-criteria web site optimization (MCWSO) problem, comprising of three criteria namely, download time, visualization score and product association level of web objects, has been addressed as a tri-objective optimization problem and solved using the vector evaluated genetic algorithm (VEGA). Experimental results show that the VEGA based MCWSO algorithm, in comparison to the GA based MCWSO algorithm, is able to select comparatively better web object sequences for a web site.

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