In their original versions, nature-inspired search algorithms such as evolutionary algorithms
and those based on swarm intelligence, lack a mechanism to deal with the constraints of a …

This paper develops a surrogate-assisted evolutionary programming (EP) algorithm for
constrained expensive black-box optimization that can be used for high-dimensional …

This article develops two new algorithms for constrained expensive black-box optimization
that use radial basis function surrogates for the objective and constraint functions. These …

This paper reviews some state-of-the-art hybrid multiobjective evolutionary algorithms
(MOEAs) dealing with multiobjective optimization problem (MOP). The mathematical …

This paper proposes a local search optimizer that, employed as an additional operator in
multiobjective evolutionary techniques, can help to find more precise estimates of the Pareto …

This paper develops a new surrogate-assisted evolutionary programming (EP) algorithm for
computationally expensive constrained black-box optimization. The proposed algorithm …

We devise in this paper a local search procedure for multiobjective genetic algorithms (GAs).
The proposed local search process employs quadratic approximations for all objective …

Real-world optimization problems are often governed by one or more constraints. Over the
last few decades, extensive research has been performed in Constrained Optimization …

In addition to inequality constraints, many mathematical models require equality constraints
to represent the practical problems appropriately. The existence of equality constraints …

This chapter provides a review of new hybrid methods that deal with the continuous local
and global optimization problems for constrained industrial production planning problems. In …