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The Scientific World Journal
Volume 2014, Article ID 734975, 9 pages
Research Article

A Local Stability Supported Parallel Distributed Constraint Optimization Algorithm

School of Information Science & Engineering, Northeastern University, Shenyang 110819, China

Received 29 April 2014; Accepted 7 June 2014; Published 3 July 2014

Academic Editor: Chin-Chia Wu

Copyright © 2014 Duan Peibo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a new distributed constraint optimization algorithm called LSPA, which can be used to solve large scale distributed constraint optimization problem (DCOP). Different from the access of local information in the existing algorithms, a new criterion called local stability is defined and used to evaluate which is the next agent whose value needs to be changed. The propose of local stability opens a new research direction of refining initial solution by finding key agents which can seriously effect global solution once they modify assignments. In addition, the construction of initial solution could be received more quickly without repeated assignment and conflict. In order to execute parallel search, LSPA finds final solution by constantly computing local stability of compatible agents. Experimental evaluation shows that LSPA outperforms some of the state-of-the-art incomplete distributed constraint optimization algorithms, guaranteeing better solutions received within ideal time.