Performance evaluation of a genetic algorithm for optimizing hierarchical menus

Hierarchical menus are now widely used as standard user interfaces in modern applications with GUIs. The menu performance depends on many factors, such as the structure, layout, and colors. There has been extensive research on novel hierarchical menus, but there has been little work on improving performance by optimizing the menu´s structure. We have proposed an algorithm based on a genetic algorithm (GA) for optimizing the performance of menus. The algorithm aims to minimize the average selection time of menu items by taking into account movement and decision-making time. We have shown that the proposed algorithm can reduce average selection time nearly 40% for a menu of a cellar phone. But usage pattern were limited and the accuracy of the model was not confirmed. We will first show the validation result of the model by experiments conducted on PDA. Then we will present results of the performance evaluation of the algorithm by using a wide variety of usage patterns generated by Zipf function. The results show that the model has good accuracy for real users, and the algorithm can attain good results for a wide variety of usage patterns.