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Performance Analysis of MADO Dynamic Optimization Algorithm

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4 Author(s)
Julien Lepagnot ; Lab. Images, Signaux et Syst. Intelligents, LISSI, Univ. de Paris 12, Creteil, France ; Amir Nakib ; Hamouche Oulhadj ; Patrick Siarry

Many real-world problems are dynamic and require an optimization algorithm that is able to continuously track a changing optimum over time. In this paper, a new multiagent algorithm for solving dynamic problems is studied. This algorithm, called MADO, is analyzed using the Moving Peaks Benchmark, and its performances are compared to those of competing dynamic optimization algorithms on several instances of this benchmark. The obtained results show the efficiency of MADO, even in multimodal environments.

Published in:

2009 Ninth International Conference on Intelligent Systems Design and Applications

Date of Conference:

Nov. 30 2009-Dec. 2 2009