Abstract
This paper compares empirically the performance in time and space of two multiobjective graph search algorithms, MOA and NAMOA. Previous theoretical work has shown that NAMOA is never worse than MOA. Now, a statistical analysis is presented on the relative performance of both algorithms in space and time over sets of randomly generated problems. © 2010 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
MacHuca, E., Mandow, L., De La Cruz, J. L. P., & Ruiz-Sepulveda, A. (2010). An empirical comparison of some multiobjective graph search algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6359 LNAI, pp. 238–245). https://doi.org/10.1007/978-3-642-16111-7_27
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