Generally, evolutionary algorithms require a large number of evaluations of the objective function in order to obtain a good solution. This paper presents a simple approach to sav...
When evolutionary algorithms are used for solving numerical constrained optimization problems, how to deal with the relationship between feasible and infeasible individuals can dir...
This paper presents a particle swarm optimizer for solving constrained optimization problems which adopts a very small population size (five particles). The proposed approach uses...
Juan Carlos Fuentes Cabrera, Carlos A. Coello Coel...
Abstract— This paper presents a comparison of four bioinspired algorithms (all seen as search engines) with a similar constraint-handling mechanism (Deb’s feasibility rules) to...
Abstract— Meta-heuristic optimization approaches are commonly applied to many discrete optimization problems. Many of these optimization approaches are based on a local search op...
In this Chapter we present the modification of a Differential Evolution algorithm to solve constrained optimization problems. The changes include a deterministic and a self-adapti...