Lp-Norm based algorithm for multi-objective distributed constraint optimization
Tenda Okimoto, Nicolas Schwind, Maxime Clément, Katsumi Inoue · Institutional Repositories DataBase (IRDB) · 2014
In this paper, we develop a novel algorithm which finds a subset of Pareto front of a Multi-Objective Distributed Constraint Optimization Problem. This algorithm utilizes the Lp-norm method, pseudo-tree, and Dynamic Programming technique. Furthermore, we show that this Lp-norm based algorithm can only guarantee to find a Pareto optimal solution, when we employ L1-norm (Manhattan norm).