Study of inheritance and approximation techniques for adaptive multi-objective Particle Swarm Optimization

In this paper, we propose to introduce inheritance and approximation techniques for the evaluation of the objective function. The main idea of the approaches is to reduce MO-TRIBES complexity. Besides, in our study, we incorporate at the beginning, an inheritance technique then an approximation technique (Approximation 1: to consider the whole swarm, Approximation 2: to consider the tribe) at the evaluation of the objective function. We conducted in our experiments eleven well-known multi-objective test functions. The results showed a good behavior of our propositions on most tested functions. Moreover, TRIBES-inheritance provided the best compared to MO-TRIBES, we concluded that MO-TRIBES with inheritance give the best time than MO-TRIBES and MO-TRIBES with approximation. It also kept the same performances with MO-TRIBES with a simple improvement for several functions.