A New Multiagent Algorithm for Dynamic Continuous Optimization-Reference-Cited by-同舟云学术

A New Multiagent Algorithm for Dynamic Continuous Optimization

Published:2010-01 Issue:1 Volume:1 Page:16-38
ISSN:1947-8283
Container-title:International Journal of Applied Metaheuristic Computing
language:en
Short-container-title:

Author:

Lepagnot Julien¹,Nakib Amir¹,Oulhadj Hamouche¹,Siarry Patrick¹

Affiliation:

1. Université de Paris 12, France

Abstract

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 is proposed to solve dynamic problems. This algorithm is based on multiple trajectory searches and saving the optima found to use them when a change is detected in the environment. The proposed algorithm is analyzed using the Moving Peaks Benchmark, and its performances are compared to competing dynamic optimization algorithms on several instances of this benchmark. The obtained results show the efficiency of the proposed algorithm, even in multimodal environments.

Publisher

IGI Global

Subject

Decision Sciences (miscellaneous),Computational Mathematics,Computational Theory and Mathematics,Control and Optimization,Computer Science Applications,Modeling and Simulation,Statistics and Probability

Reference30 articles.

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