Performance analysis of MADO dynamic optimization algorithm

被引：5

作者：

Lepagnot, Julien ^{[1
]}

Nakib, Amir ^{[1
]}

Oulhadj, Hamouche ^{[1
]}

Siarry, Patrick ^{[1
]}

机构：

[1] Univ Paris 12, Lab Images Signaux & Syst Intelligents, LISSI, EA 3956, F-94010 Creteil, France

来源：

2009 9TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS | 2009年

关键词：

dynamic; non-stationary; time-varying; continuous; optimization; multiagent; metaheuristic; Moving Peaks; SWARM OPTIMIZATION; EVOLUTION;

D O I：

10.1109/ISDA.2009.35

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：37 / 42

页数：6

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