A Genetic Algorithm Approach for Optimizing a Single-Finger Arabic Keyboard Layout

Abstract

The use of cellphones and handheld devices in our daily activities is not limited to making calls or writing short text messages. The added features of wireless technology and related applications made it possible to write emails, notes and long text. Nevertheless, the currently used keyboards in portable devices are not optimized for such use, in terms of rapid and ergonomic typing. In this research, we aim to optimize the design of the Arabic keyboard layout for applications that predominantly use a single pointer, such as those used in portable devices. The main objective is to find the best single-finger Arabic keyboard layout that allows users of portable devices to write text and carry out written conversations for a long time with comfort, ease, and speed. Since the single-finger keyboard layout problem can be modeled in terms of the famous Quadratic Assignment Problem (QAP), which is known to be NP-hard, heuristics and meta-heuristics are recommended for solving such problem. To adapt the problem to the requirements of optimizing the single-finger Arabic keyboard, we added two measures to the classical—distance based—objective function of the QAP, which are: the keyboard row weight and the hit direction of the finger. A Genetic Algorithm (GA) approach with two different crossover types (two-point and modified uniform crossovers), and three different mutation operators (swap, insertion, and Simulated Annealing (SA)) was developed and thoroughly tested. The experimental results demonstrated that the simple swap mutation produced better results than the other mutations, with both crossover types. Moreover, experimental testing has shown that the added measures in the objective function had a positive effect, in terms of improving the typing speed, when compared to the original QAP objective function. Finally, comparing the resulting optimized keyboard layout with other existing keyboards showed that our keyboard layout is favorable, in terms of the optimization criteria considered in this research, than the other layouts tested.