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Concurrent Differential Evolution for Uncertain Optimization Problems

Authors:
Kiyoharu Tagawa
Takashi Ishimizu

Keywords: evolutionary algorithm; concurrent program; uncertain optimization problem; differential evolution.

Abstract:
Multi-core CPUs, which have more than one processor (core), have been introduced widely into personal computers. Therefore, in order to utilize the additional cores to execute various costly application programs, concurrent implementations of them have been paid attention to. In this paper, a concurrent program of the latest evolutionary algorithm, i.e., differential evolution, is described. Furthermore, the concurrent program of differential evolution, which is called concurrent differential evolution, is revised to reduce the computational time for solving optimization problems in the presence of a wide range of uncertainties. Many real-world applications can be formulated as an uncertain optimization problem in which a probabilistic objective function has to be evaluated by using Monte Carlo integration. Consequently, it usually takes a long computational time to solve the uncertain optimization problem. The results of the numerical experiments conducted on two classes of uncertain optimization problems show that the revised version can reduce the computational time apparently comparing with the conventional version.

Pages: 48 to 53

Copyright: Copyright (c) IARIA, 2011

Publication date: November 20, 2011

Published in: conference

ISSN: 2308-4499

ISBN: 978-1-61208-172-4

Location: Lisbon, Portugal

Dates: from November 20, 2011 to November 25, 2011