Memetic algorithm with Local search chaining for large scale continuous optimization problems

Abstract— Memetic algorithms arise as very effective algorithms to obtain reliable and high accurate solutions for complex continuous optimization problems. Nowadays, high dimensional optimization problems are an interesting field of research. The high dimensionality introduces new problems for the optimization process, making recommendable to test the behavior of the optimization algorithms to large-scale problems. The Local search method must be applied with a higher intensity, specially to most promising solutions, to explore the higher domain space around each solution. In this work, we present a preliminar study of a memetic algorithm that assigns to each individual a local search intensity that depends on its features, by chaining different local search applications. This algorithm have obtained good results in continuous optimization and we study whether is a good algorithm for large scale optimizations problems. We make experiments of our proposal using the benchmark problem...

• Type: Conference
• Year: 2009
• Where: CEC
• Authors: Daniel Molina, Manuel Lozano, Francisco Herrera
• Keywords: Algorithm, CEC 2009, Local Search, Memetic Algorithm