Optimizing hierarchical menus by genetic algorithm and simulated annealing

Abstract

Hierarchical menus are now ubiquitous. The performance of the menu depends on many factors: structure, layout, colors and so on. There has been extensive research on novel menus, but there has been little work on improving performance by optimizing the menu's structure. This paper proposes algorithms based on the genetic algorithm (GA) and the simulated annealing (SA) for optimizing the performance of menus. The algorithms aim to minimize the average selection time of menu items by considering the user's pointer movement and search/decision time. We will show the experimental results on a static hierarchical menu of a cellular phone as an example where a small screen and limited input device are assumed. We will also show performance comparison of the GAbased algorithm and the SA-based one by using wide varieties of usage patterns.

Command Selection

“…These models should be able to provide a preliminary evaluation of a specific design. They should also be introduced in optimization methods (Dayama et al 2021;Bailly et al 2013a;Matsui and Yamada 2008) to explore in a systematic way the design space of command selection.…”

Combinatorial Optimization of Graphical User Interface Designs

“…3) Hierarchical Menus: Matsui and Yamada [141], [142] represented a hierarchical cell-phone menu as a tree structure. They used simulated annealing (SA) to optimize it for selection time with a mixture of logarithmic pointing time and number of items.…”

“…Typically, the probability is exp(−βΔ), where Δ is the difference in objective value and β a parameter referred to as inverse temperature. In this domain, SA has been applied for menu hierarchy design [142] and other uses. Further members of this class used in GUI design have been evolutionary algorithms [141], [166] and ant colony optimization [58].…”