The Automatic Dynamic Penalisation method (ADP) for handling constraints with genetic algorithms

摘要: In this paper we present a new penalty-based approach, developed within the framework of genetic algorithms (GAs) for constrained optimisation problems. The proposed technique, which is called Automatic Dynamic Penalisation (ADP) method, belongs to category exterior strategies. aim work consists in providing simple and effective constraint-handling technique without need tuning penalty coefficients values any considered problem. key-concept that underlies ADP strategy it possible exploit information restrained population, at current generation, order guide search through whole definition domain give proper evaluation coefficients. firstly applied three different benchmark problems obtained results are compared those available literature show effectiveness technique. Finally, as examples real-world engineering applications, method employed solution two problems, i.e. optimal design damping properties hybrid elastomer/composite laminates maximisation first buckling load composite with given elastic symmetries.