1

1. Few parameters setting required – Np, F, Cr
2. Searches randomly
3. It has high performance
4. It can be accessible for practical applications
5. It is easy to use
6. simple concept involved
7. speed to get solutions

4.2 Disadvantages of DE
DE however has it’s drawback (Tonge ; Kulkarni 2012) and (Das ; Suganthan 2011) such as:
1. It is easy to drop into regional optimum
2. It has unstable convergence.
3. It can be outperformed by CMA-ES, on functions that are not linearly separable

4.3 Applications of DE
A worth while tool for measuring an algorithmic performance is a multi-modal function test bed. The effect of dimension, epistasis, the number of local optima and other variables on an optimizer’s performance is known easily by test functions.