NDLI: Visualizing multi-dimensional pareto-optimal fronts with a 3D virtual reality system

Content Provider	IEEE Xplore Digital Library
Author	Madetoja, E. Ruotsalainen, H. Monkkonen, V.-M. Hamalainen, J. Deb, K.
Copyright Year	2008
Description	Author affiliation: Dept. of Physic, Univ. of Kuopio, Kuopio (Madetoja, E.; Ruotsalainen, H.; Monkkonen, V.-M.; Hamalainen, J.) \|\| Dept. of Bus. Technol., Helsinki Sch. of Econ., Helsinki (Deb, K.)
Abstract	In multiobjective optimization, there are several targets that are in conflict, and thus they all cannot reach their optimum simultaneously. Hence, the solutions of the problem form a set of compromised trade-off solutions (a Pareto-optimal front or Pareto-optimal solutions) from which the best solution for the particular problem can be chosen. However, finding that best compromise solution is not an easy task for the human mind. Pareto-optimal fronts are often visualized for this purpose because in this way a comparison between solutions according to their location on the Pareto-optimal front becomes somewhat easier. Visualizing a Pareto-optimal front is straightforward when there are only two targets (or objective functions), but visualizing a front for more than two objective functions becomes a difficult task. In this paper, we introduce a new and innovative method of using three-dimensional virtual reality (VR) facilities to present multi-dimensional Pareto-optimal fronts. Rotation, zooming and other navigation possibilities of VR facilities make easy to compare different trade-off solutions, and fewer solutions need to be explored in order to understand the interrelationships among conflicting objective functions. In addition, it can be used to highlight and characterize interesting features of specific Pareto-optimal solutions, such as whether a particular solution is close to a constraint boundary or whether a solution lies on a relatively steep trade-off region. Based on these additional visual aids for analyzing trade-off solutions, a preferred compromise solution may be easier to choose than by other means.
Starting Page	907
Ending Page	913
File Size	1313956
Page Count	7
File Format	PDF
ISBN	9788360810149
ISSN	18967094
DOI	10.1109/IMCSIT.2008.4747350
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-20
Publisher Place	Poland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer science Visualization Navigation Decision making Humans Optimization methods Virtual reality Data mining Information technology Physics
Content Type	Text
Resource Type	Article

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