Bounded Max-Sum is a message-passing algorithm for solving Distributed Constraint Optimization Problems able to compute solutions with a guaranteed approximation ratio. Although its approximate solutions were empirically proved to be within a small percentage of the optimal solution on low and moderately dense problems, in this paper we show that its theoretical approximation ratio is overestimated, thus overshadowing its good performance. We propose a new algorithm, called Improved Bounded Max-Sum, whose approximate solutions are at least as good as the ones found by Bounded Max-Sum and with a tighter approximation ratio. Our empirical evaluation shows that the new approximation ratio is significantly tighter. © 2012 Springer-Verlag.
CITATION STYLE
Rollon, E., & Larrosa, J. (2012). Improved bounded max-sum for distributed constraint optimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7514 LNCS, pp. 624–632). https://doi.org/10.1007/978-3-642-33558-7_45
Mendeley helps you to discover research relevant for your work.