The multiagent optimization system (MAOS) supports the cooperative search by self-organization of multiple agents situated in an environment with certain sharing public knowledge. Each agent in MAOS is an autonomous entity with individual memory and behavioral components. Based on the MAOS framework, some efficient knowledge components for solving the traveling salesman problem (TSP) are implemented. The experimental results on TSP benchmark data sets show that MAOS-TSP  could achieve optimal solutions very efficiently for large-scale instances, and is competitive as compared with state-of-the-art algorithms.
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 X.-F. Xie, J. Liu. Multiagent optimization system for solving the traveling salesman problem (TSP). IEEE Transactions on Systems, Man, and Cybernetics - Part B, 2009, 39(2): 489-502. [PDF]