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Solving Global Optimization Problems Using MANGO

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 5559)


Traditional approaches for solving global optimization problems generally rely on a single algorithm. The algorithm may be hybrid or applied in parallel. Contrary to traditional approaches, this paper proposes to form teams of algorithms to tackle global optimization problems. Each algorithm is embodied and ran by a software agent. Agents exist in a multiagent system and communicate over our proposed MultiAgent ENvironment for Global Optimization (MANGO). Through communication and cooperation, the agents complement each other in tasks that they cannot do on their own. This paper gives a formal description of MANGO and outlines design principles for developing agents to execute on MANGO. Our case study shows the effectiveness of multiagent teams in solving global optimization problems.


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  • Global Optimization
  • Multiagent System
  • Trust Region
  • Global Optimization Problem

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This research has been partially supported by the Scientific and Technological Research Council of Turkey by a CAREER Award under grant 107M455. A preliminary version of this paper appeared at AAMAS OPTMAS Workshop 2008.

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© 2009 Springer-Verlag Berlin Heidelberg

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Günay, A., Öztoprak, F., Birbil, Ş.İ., Yolum, P. (2009). Solving Global Optimization Problems Using MANGO. In: Håkansson, A., Nguyen, N.T., Hartung, R.L., Howlett, R.J., Jain, L.C. (eds) Agent and Multi-Agent Systems: Technologies and Applications. KES-AMSTA 2009. Lecture Notes in Computer Science(), vol 5559. Springer, Berlin, Heidelberg.

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01664-6

  • Online ISBN: 978-3-642-01665-3

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