Computational geometry: an introduction
Computational geometry: an introduction
Computational geometry: algorithms and applications
Computational geometry: algorithms and applications
Data Structures for Range Searching
ACM Computing Surveys (CSUR)
Multidimensional binary search trees used for associative searching
Communications of the ACM
Computation of robust Pareto points
International Journal of Computing Science and Mathematics
Symbolic archive representation for a fast nondominance test
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Maxima-finding algorithms for multidimensional samples: A two-phase approach
Computational Geometry: Theory and Applications
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We propose a new data structure for the efficient computation of the nondominance problem which occurs in most multi-objective optimization algorithms. The strength of our data structure is illustrated by a comparison both to the linear list approach and the quad tree approach on a category of problems. The computational results indicate that our method is particularly advantageous in the case where the proportion of the nondominated vectors versus the total set of criterion vectors is not too large.