@inproceedings{2006007,
abstract = {Diversity maintenance of solutions is an essential part in multi-objective optimization. Existing techniques are suboptimal either in the sense of obtained distribution or execution time. This paper proposes an effective and relatively fast method for pruning a set of nondominated solutions. The proposed method is based on a crowding estimation technique using nearest neighbors of solutions in Euclidean sense, and a technique for finding these nearest neighbors quickly. The method is experimentally evaluated, and results indicate a good trade-off between the obtained distribution and execution time. Distribution is good also in many-objective problems, when number of objectives is more than two. {\textcopyright} Springer-Verlag Berlin Heidelberg 2006.},
author = {Kukkonen, Saku and Deb, Kalyanmoy},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/11844297_56},
isbn = {3540389903},
issn = {16113349},
pages = {553--562},
publisher = {Springer, Berlin, Heidelberg},
title = {{A fast and effective method for pruning of non-dominated solutions in many-objective problems}},
url = {https://link.springer.com/chapter/10.1007/11844297{\_}56},
volume = {4193 LNCS},
year = {2006}
}