Abstract
It is known that the evolutional computing methods hybridized with local search methods, which are called Memetic Algorithm, are efficient as global optimization methods. The memetic algorithms are divided into two classes of hybridization strategies, which are called Baldwinian and Lamarchian types. This paper is concerned with computational considerations for these two types of hybridization strategies in a case when Particle Swarm Optimization is used as evolutional algorithm from the standpoint of global optimization methods. Especially, applications to optimization problems with constraints described by disconnected plural sets, which are difficult to solve by usual methods, are considered.
