Multiagent Optimization System (MAOS)
The Multiagent Optimization System (MAOS) [Project Portal] consists of a group of compact agents cooperating with their peers in a sharing environment for realizing a common intention of finding high-quality solution(s) based on the internal representation of the optimization task.
Some algorithms, including Particle Swarm Optimization (PSO), Differential Evolution (DE), Social Cognitive Optimization (SCO), and Electromagnetism-like Mechanism (EM) Heuristic, etc, have been implemented in the Swarm Algorithm Framework (SWAF) for solving Numerical Optimization Problem (NOP). A simplified example of the MAOS is the Mini-Swarm System, which has been applied on some combinatorial optimization problems, such as Travelling Salesman Problem (TSP), Graph Coloring Problem (GCP), Quadratic Knapsack Problem (QKP), Flow-Shop Scheduling Problem (FSP), Quadratic Assignment Problem (QAP), etc.
Xiao-Feng Xie. Round-table group optimization for sequencing problems. International Journal of Applied Metaheuristic Computing, 2012, 3(4): 1-24. [DOI]
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]
Xiao-Feng Xie, Jiming Liu. Graph coloring by multiagent fusion search. Journal of Combinatorial Optimization, 2009, 18(2): 99-123. [DOI]
Xiao-Feng Xie, Jiming Liu. A mini-swarm for the quadratic knapsack problem. IEEE Swarm Intelligence Symposium (SIS), Honolulu, HI, USA, 2007: 190-197. [DOI]
Xiao-Feng Xie, Jiming Liu. How autonomy oriented computing (AOC) tackles a computationally hard optimization problem. International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), Hakodate, Japan, 2006: 646-653. [DOI]
Xiao-Feng Xie, Jiming Liu. A compact multiagent system based on autonomy oriented computing, IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT), Compiégne, France, 2005: 38-44 [DOI]
Xiao-Feng Xie, Wen-Jun Zhang. SWAF: swarm algorithm framework for numerical optimization. Genetic and Evolutionary Computation Conference (GECCO), LNCS 3102, Seattle, WA, USA, 2004: 238-250. [SpringerLink]
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