This paper presents a new distributed constraint optimization algorithm called LSPA, which can be used to solve large scale\ndistributed constraint optimization problem (DCOP). Different from the access of local information in the existing algorithms,\na new criterion called local stability is defined and used to evaluate which is the next agent whose value needs to be changed. The\npropose of local stability opens a new research direction of refining initial solution by finding key agents which can seriously effect\nglobal solution once they modify assignments. In addition, the construction of initial solution could be received more quickly\nwithout repeated assignment and conflict. In order to execute parallel search, LSPA finds final solution by constantly computing\nlocal stability of compatible agents. Experimental evaluation shows that LSPA outperforms some of the state-of-the-art incomplete\ndistributed constraint optimization algorithms, guaranteeing better solutions received within ideal time.
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