TY - JOUR
T1 - A generalization of the averaged hausdorff distance
AU - Vargas, Andrés
AU - Bogoya, Johan
N1 - Publisher Copyright:
© 2018 Instituto Politecnico Nacional. All rights reserved.
PY - 2018
Y1 - 2018
N2 - The averaged Hausdorff distance ?p is an inframetric which has been recently used in evolutionary multiobjective optimization (EMO). In this paper we introduce a new two-parameter performance indicator ?p,q which generalizes ?p as well as the standard Hausdorff distance. For p, q 1 the indicator ?p,q (that we call the (p, q)-averaged distance) turns out to be a proper metric and preserves some of the ?p advantages. We proof several properties of ?p,q, and provide a comparison with ?p and the standard Hausdorff distance. For simplicity we restrict ourselves to finite sets, which is the most common case, but our results can be extended to the continuous case.
AB - The averaged Hausdorff distance ?p is an inframetric which has been recently used in evolutionary multiobjective optimization (EMO). In this paper we introduce a new two-parameter performance indicator ?p,q which generalizes ?p as well as the standard Hausdorff distance. For p, q 1 the indicator ?p,q (that we call the (p, q)-averaged distance) turns out to be a proper metric and preserves some of the ?p advantages. We proof several properties of ?p,q, and provide a comparison with ?p and the standard Hausdorff distance. For simplicity we restrict ourselves to finite sets, which is the most common case, but our results can be extended to the continuous case.
KW - Averaged Hausdorff distance
KW - Generational distance
KW - Inverted generational distance
KW - Multiobjective optimization
KW - Performance indicator
KW - Power means
UR - https://www.scopus.com/pages/publications/85049827763
U2 - 10.13053/cys-22-2-2950
DO - 10.13053/cys-22-2-2950
M3 - Article
AN - SCOPUS:85049827763
SN - 1405-5546
VL - 22
SP - 331
EP - 345
JO - Computacion y Sistemas
JF - Computacion y Sistemas
IS - 2
ER -