A local stability supported parallel distributed constraint optimization algorithm.
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...
| Publicado en: | Scientific World Journal pp. 734975 - 734976 |
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| Autores principales: | , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=109674935&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109674935 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1537744X 1BX5 jtl: Scientific World Journal issn: 1537744X maglogo: N pubinfo: dt: 2014 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 109674935 109674935 NLM25105166 2012676924 10.1155/2014/734975 NLM25105166 109674935 ppf: 734975 ppct: 1 formats: tig: atl: A local stability supported parallel distributed constraint optimization algorithm. aug: au: Peibo, Duan Changsheng, Zhang Bin, Zhang sug: ab: 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. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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