Fitness inheritance in multi-objective particle swarm optimization

In this paper, we propose to incorporate the concept of fitness inheritance into a multi-objective particle swarm optimizer previously proposed by us, in order to reduce the number of function evaluations performed. Four well-known test functions taken from the multi-objective optimization literature are used to evaluate the performance of the proposed approach. The results indicate a very good performance of the fitness inheritance technique, mainly when it is applied with a low probability, in which case the quality of the obtained results is even improved.