JOURNAL OF COMPUTERS (JCP)
ISSN : 1796-203X
Volume : 4    Issue : 2    Date : February 2009

A Robust Archived Differential Evolution Algorithm for Global Optimization Problems
Zhangjun Huang, Cheng-en Wang, and Mingxu Ma
Page(s): 160-167
Full Text:
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Abstract
A robust archived differential evolution algorithm is put forward by means of embedding a flexibility
processing operator and an efficiency processing operator based on original DE and ADE. A
special constraint-handling mechanism based on dynamic penalty functions and fitness calculation
of individuals is adopted in the proposed method to deal with various constraints effectively, which
is further extended by means of a flexibility processing operator so as to make it suitable for different
type problems, including those with or without constraint(s) and those with continuous, discrete or
mixed discrete-continuous variables. Furthermore, an archive of solutions is maintained during the
evolutionary process so as to keep the useful information of previous solutions and local optima for
the estimation of new solutions. Based on the archive of solutions, an iterative control operator and
an efficiency processing operator are designed in the algorithm. The former guides the evolutionary
process towards a promising search space, avoiding unnecessary and worthless search. The latter
improves the local searching efficiency and the final searching quality. Experimental results based
on a suite of six well-known optimization problems reveal that the proposed algorithm is robust,
effective, efficient and suitable for different type global optimization problems.

Index Terms
Global optimization, differential evolution, constraint handling, archived solutions, iterative control