Large Neighborhood Search with Quality Guarantees for Distributed Constraint Optimization Problems

Abstract. The field of Distributed Constraint Optimization has gained momentum in recent years, thanks to its ability to address various applications related to multi-agent cooperation. Nevertheless, solving Distributed Constraint Optimization Problems (DCOPs) optimally is NP-hard. Therefore, in large-scale applications, incomplete DCOP algorithms are desirable. Current incomplete search techniques have subsets of the following limitations: (a) they find local minima without quality guarantees; (b) they provide loose quality assessment; or (c) they cannot exploit certain problem structures such as hard constraints. Therefore, capitalizing on strategies from the centralized constraint reasoning community, we propose to adapt the Large Neighborhood Search (LNS) strategy to solve DCOPs, resulting in the general Distributed LNS (D-LNS) framework. The characteristics of this framework are as follows: (i) it is anytime; (ii) it provides quality guarantees by refining online upper and lowe...

• Type: Journal
• Year: 2015
• Where: ATAL
• Authors: Ferdinando Fioretto, Federico Campeotto, Agostino Dovier, Enrico Pontelli, William Yeoh 0001
• Keywords: ATAL 2015, Intelligent Agents