Application of a seeded hybrid genetic algorithm for user interface design

Authors

Nicholas S. Hardman, Air Force Institute of Technology
John M. Colombi, Air Force Institute of Technology
David R. Jacques, Air Force Institute of Technology
Raymond R. Hill, Air Force Institute of Technology
Janet E. Miller, 711th Human Performance Wing

Document Type

Conference Proceeding

Publication Date

11-9-2009

Abstract

Studies have established that computer user interface (UI) design is a primary contributor to people's experiences with modern technology; however, current UI development remains more art than quantifiable science. In this paper, we study the use of search algorithms to predict optimal display layouts early in system design. This has the potential to greatly reduce the cost and improve the quality of UI development. Specifically, we demonstrate a hybrid genetic algorithm and pattern search optimization process that makes use of human performance modeling to quantify known design principles. We show how this approach can be tailored by capturing contextual factors in order to properly seed and tune the genetic algorithm. Finally, we demonstrate the ability of this process to discover superior layouts as compared to manual qualitative methods. Abstract © IEEE

Comments

Copyright © 2009, IEEE

Co-author N. Hardman was an AFIT PhD student at the time of this paper. (AFIT-DS-ENV-09-D01, December 2009)

DOI

10.1109/ICSMC.2009.5346789

Source Publication

IEEE International Conference on Systems, Man and Cybernetics, 2009. SMC 2009.

Recommended Citation

N. Hardman, J. Colombi, D. Jacques, R. Hill and J. Miller, "Application of a seeded hybrid genetic algorithm for user interface design," 2009 IEEE International Conference on Systems, Man and Cybernetics, San Antonio, TX, USA, 2009, pp. 462-467, doi: 10.1109/ICSMC.2009.5346789.