OPTIMIZATION APPLICATIONS WITH MULTIMODAL TEST FUNCTION COMPARISON

This paper attempts to put up a general review of common knowledge of dis-similar types of the intelligent optimization process, controlling techniques and algorithms like that swarm optimization or PSO. In this algorithm, we are deploying two models called as global – best and local – best, and hence we consider these models as in multimodal test functions.  At last, the studies and results show that the methods are very highly competitive and also can be used as a suitable another approach to solving the problem of multi-object optimization when dealing with multimodal functions. We study different uncertainties from present approaches to addressing them and relationship of different processes is discussed. At last, we would like to propose some promising points are suggested for future research purpose.