Collaboration of Metaheuristic Algorithms through a Multi-Agent System
作者： Richard Malek
DOI: 10.1007/978-3-642-03668-2_7
关键词:
摘要: This paper introduces a framework based on multi-agent system for solving problems of combinatorial optimization. The allows running various metaheuristic algorithms simultaneously. By the collaboration metaheuristics, we can achieve better results in more classes problems.
springer.com
harvard.edu
springerlink.com参考文章(10)
David B. Fogel, Zbigniew Michalewicz, Thomas Back, Handbook of Evolutionary Computation ,(1997)
Xin-She Yang, Nature-Inspired Metaheuristic Algorithms ,(2008)
Edmund Burke, Graham Kendall, Jim Newall, Emma Hart, Peter Ross, Sonia Schulenburg, Hyper-Heuristics: An Emerging Direction in Modern Search Technology Handbook of Metaheuristics. pp. 457- 474 ,(2003) , 10.1007/0-306-48056-5_16
Mutsunori Yagiura, Toshihide Ibaraki, On metaheuristic algorithms for combinatorial optimization problems Systems and Computers in Japan. ,vol. 32, pp. 33- 55 ,(2001) , 10.1002/1520-684X(200103)32:3<33::AID-SCJ4>3.0.CO;2-P
D. Sislak, M. Rehak, M. Pechoucek, A-globe: Multi-Agent Platform with Advanced Simulation and Visualization Support web intelligence. pp. 805- 806 ,(2005) , 10.1109/WI.2005.18
D.B. Fogel, Phenotypes, genotypes, and operators in evolutionary computation ieee international conference on evolutionary computation. ,vol. 1, pp. 193- ,(1995) , 10.1109/ICEC.1995.489143
E.-G. Talbi, A Taxonomy of Hybrid Metaheuristics Journal of Heuristics. ,vol. 8, pp. 541- 564 ,(2002) , 10.1023/A:1016540724870
D.H. Wolpert, W.G. Macready, No free lunch theorems for optimization IEEE Transactions on Evolutionary Computation. ,vol. 1, pp. 67- 82 ,(1997) , 10.1109/4235.585893
Steven S. Skiena, The Algorithm Design Manual ,(1980)
M. Milano, A. Roli, MAGMA: a multiagent architecture for metaheuristics systems man and cybernetics. ,vol. 34, pp. 925- 941 ,(2004) , 10.1109/TSMCB.2003.818432