An Empirical Comparison of Some Multiobjective Graph Search Algorithms

Enrique Machuca, Lawrence Mandow, J.L. Pérez De La Cruz, and A. Ruiz-Sepulveda.
An empirical comparison of some multiobjective graph search algorithms.
In Rodiger Dillmann, Jorgen Beyerer, Uwe Hanebeck, and Tanja Schultz, editors, KI 2010: Advances in Artificial Intelligence, volume 6359 of Lecture Notes in Computer Science, pages 238-245. Springer Berlin / Heidelberg, 2010. 10.1007/978-3-642-16111-7_27.


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.


  affiliation={Universidad de M{\'a}laga Dpto. Lenguajes y Ciencias de la Computaci{\'o}n 29071 M{\'a}laga Spain},
  keyword={Computer Science},
  url={http: //},
  author={Machuca, Enrique and Mandow, Lawrence and P{\'e}rez De La Cruz, J.L. and Ruiz-Sepulveda, A.},
  title={An Empirical Comparison of Some Multiobjective Graph Search Algorithms},
  editor={Dillmann, Rodiger and Beyerer, Jorgen and Hanebeck, Uwe and Schultz, Tanja},
  booktitle={KI 2010: Advances in Artificial Intelligence},
  series={Lecture Notes in Computer Science},
  publisher={Springer Berlin / Heidelberg},
Redmine Appliance - Powered by TurnKey Linux