Modified Chimp Optimization Algorithm Based On Classical Conjugate Gradient Methods

In this paper, a new hybrid algorithm was proposed for the chimp algorithm using another traditional efficient algorithm called the Conjugate Gradient Algorithm called (CGA). The algorithm CG works to optimize the randomly created elementary community as the basic community of chimp optimization algorithms by using the characteristic traditional algorithm above. The test was applied to (10) high-efficiency optimization functions with different dimensions and frequency. The results of the hybrid algorithm were excellent, encouraging, and superior to the original algorithm. The hybrid algorithm achieved optimal solutions by reaching to a minimum value (f_min) for most of these functions.