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Optimizing hierarchical menus by genetic algorithm and simulated annealing
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Genetic And Evolutionary Computation Conference archive
Proceedings of the 10th annual conference on Genetic and evolutionary computation table of contents
Atlanta, GA, USA
SESSION: Real-world application papers table of contents
Pages 1587-1594  
Year of Publication: 2008
ISBN:978-1-60558-130-9
Authors
Shouichi Matsui  CRIEPI, Komae, Tokyo, Japan
Seiji Yamada  National Institute of Informatics, Chiyoda, Tokyo, Japan
Sponsors
ACM: Association for Computing Machinery
SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
Publisher
ACM  New York, NY, USA
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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 GA-based algorithm and the SA-based one by using wide varieties of usage patterns.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Collaborative Colleagues:
Shouichi Matsui: colleagues
Seiji Yamada: colleagues