This paper provides a comprehensive survey of the most popular constraint-handling
techniques currently used with evolutionary algorithms. We review approaches that go from …

Structural health monitoring plays an increasingly significant role in detecting damages for
large and complex structures to ensure their serviceability and sustainability. Optimal sensor …

No pleasure lasts long unless there is variety in it. Publilius Syrus, Moral Sayings We've
been very fortunate to receive fantastic feedback from our readers during the last four years …

This paper introduces the notion of using co-evolution to adapt the penalty factors of a
fitness function incorporated in a genetic algorithm (GA) for numerical optimization. The …

In this paper, we propose a dominance-based selection scheme to incorporate constraints
into the fitness function of a genetic algorithm used for global optimization. The approach …

Genetic Algorithms are most directly suited to unconstrained optimization. Application of
Genetic Algorithms to constrained optimization problems is often a challenging effort …

During the last five years, several methods have been proposed for handling nonlinear
constraints using evolutionary algorithms (EAs) for numerical optimization problems. Recent …

Design is a complex engineering activity, in which computers are more and more involved.
The design task can often be seen as an optimization problem in which the parameters or …

In this paper, a new real coded crossover operator, called the Laplace Crossover (LX) is
proposed. LX is used in conjunction with two well known mutation operators namely the …

In this paper, a new mutation operator called power mutation (PM) is introduced for real
coded genetic algorithms (RCGA). The performance of PM is compared with two other …