Work on leveraging optimization with mixed individual and social learning appears on Applied Soft Computing

Work on leveraging optimization with mixed individual and social learning appears on Applied Soft Computing

Our work on leveraging optimization with mixed individual and social learning in CGO appears on Applied Soft Computing. You can free access to the article through this link. X.-F. Xie, Z.-J. Wang. Cooperative group optimization with ants (CGO-AS): Leverage optimization with mixed individual and social learning. Applied Soft Computing, 2017, 50: 223-234. [DOI] We present CGO-AS, a generalized Ant System (AS) implemented in the framework of Coopera

Presented our work on combinatorial optimization at International Joint Conference on Artificial Intelligence (IJCAI)

Presented our work on combinatorial optimization at International Joint Conference on Artificial Intelligence (IJCAI)

We presented our work on exploiting problem structure in combinatorial landscapes at the 25th International Joint Conference on Artificial Intelligence (IJCAI), New York. X.-F. Xie, Z.-J. Wang. Exploiting problem structure in combinatorial landscapes: A case study on pure mathematics application. International Joint Conference on Artificial Intelligence (IJCAI), New York, NY, USA, 2016: 2683-2689.   IJCAI is the premier conference bringing togeth

Work on Smart Urban Traffic Control published on Transportation Research Part C

Work on Smart Urban Traffic Control published on Transportation Research Part C

Schedule-driven intersection control (SchIC) is the core control engine (the brain) of the smart and scalable urban traffic control system (SurTrac). X.-F. Xie, S. Smith, L. Lu, G. Barlow. Schedule-driven intersection control. Transportation Research Part C: Emerging Technologies, 2012, 24: 168-189. [DOI] Model-based intersection optimization strategies have been widely investigated for distributed traffic signal control in road networks. Due to

Work on solving the Traveling Saleman Problem was published on IEEE Trans. on SMC-B

Work on solving the Traveling Saleman Problem was published on IEEE Trans. on SMC-B

MAOS-TSP is a cooperative group optimization system for solving the Traveling Salesman Problem (TSP). It has been tested and achieved optimal solutions efficiently for large-scale instances. The code can be downloaded here.  Xiao-Feng Xie, Jiming Liu. Multiagent optimization system for solving the traveling salesman problem (TSP). IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2009, 39(2): 489-502. [DOI] Abstract: The mu

Work on solving the Graph Coloring Problem was published on Journal of Combinatorial Optimization

Work on solving the Graph Coloring Problem was published on Journal of Combinatorial Optimization

MAOS-GCP is a cooperative group optimization system for solving the Graph Coloring Problem (GCP). It has been tested and achieved optimal solutions efficiently for large-scale instances. The binary code can be downloaded from the portal. Xiao-Feng Xie, Jiming Liu. Graph coloring by multiagent fusion search. Journal of Combinatorial Optimization, 2009, 18(2): 99-123. [DOI] Abstract: A multiagent fusion search is presented for the graph coloring pr