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JACIII Vol.4 No.2 pp. 164-170
doi: 10.20965/jaciii.2000.p0164
(2000)

Paper:

An Adaptive Penalty Function Method for Constrained Optimization with Evolutionary Programming

Xinghuo Yu and Baolin Wu

Faculty of Informatics and Communication Central Queensland University Rockhampton Qld 4702, Australia

Received:
March 15, 1999
Accepted:
July 20, 1999
Published:
March 20, 2000
Keywords:
Evolutionary computation, Constraints, Fuction optimization, Penalty, Search
Abstract

In this paper, we propose a novel adaptive penalty function method for constrained optimization problems using the evolutionary programming technique. This method incorporates an adaptive tuning algorithm that adjusts the penalty parameters according to the population landscape so that it allows fast escape from a local optimum and quick convergence toward a global optimum. The method is simple and computationally effective in the sense that only very few penalty parameters are needed for tuning. Simulation results of five well-known benchmark problems are presented to show the performance of the proposed method.

Cite this article as:
X. Yu and B. Wu, “An Adaptive Penalty Function Method for Constrained Optimization with Evolutionary Programming,” J. Adv. Comput. Intell. Intell. Inform., Vol.4, No.2, pp. 164-170, 2000.
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Last updated on Dec. 01, 2020