Abstract
Several metrics and indicators have been suggested in the past to evaluate multi-objective evolutionary and non-evolutionary algorithms. However, these metrics are known to have many problems that make their application sometimes unsound, and sometimes infeasible. This paper proposes a new approach, in which metrics are parameterized with respect to a reference set, on which depend the properties of any metric.
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Mohan, C.K., Mehrotra, K.G. (2011). Reference Set Metrics for Multi-Objective Algorithms. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2011. Lecture Notes in Computer Science, vol 7076. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27172-4_85
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DOI: https://doi.org/10.1007/978-3-642-27172-4_85
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27171-7
Online ISBN: 978-3-642-27172-4
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