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A Simple Evolution Strategy to Solve Constrained Optimization Problems
Efrén Mezura-Montes and Carlos A. Coello Coello
CINVESTAV-IPN
Evolutionary Computation Group (EVOCINV)
Departamento de Ingeniería Eléctrica
Sección de Computación
Av. Instituto Politécnico Nacional No. 2508
Col. San Pedro Zacatenco
México D.F. 07300, MÉXICO
emezura@computacion.cs.cinvestav.mx
ccoello@cs.cinvestav.mx
Abstract.
In this paper, we argue that the self-adaptation mechanism of
a conventional evolution strategy combined with some (very simple)
tournament rules based on feasibility similar to some previous proposals
(e.g., [1])
can provide us with a
highly competitive evolutionary algorithm for constrained
optimization.
In our proposal, however, no extra mechanisms
are provided to maintain diversity.
In order to verify our hypothesis,
we performed a small comparative study among five
different types of ES:
-ES with and without correlated mutation
and a 
-ES using the "
-success rule".
The tournament rules adopted in the five types of ES implemented
are the following: Between 2 feasible solutions, the one with the
highest fitness value wins, if one solution is feasible and the other
one is infeasible, the feasible solution wins and if both solutions are
infeasible, the one with the lowest sum of constraint violation is preferred.
To evaluate the performance of the five types of ES under
study, we decided to use ten (out of 13)
of the test functions described
in [2].
The 
had the
best overall performance (both in terms of the best solution found
and in terms of its statiscal measures).
The algorithm of the type of ES adopted (due to its simplicity,
we decided to call it Simple Evolution Strategy, or SES) is presented in
Figure 1.
LNCS 2723, p. 640 f.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2003