About convergence rate and solution precision are not high in high-dimensional Nonlinear Optimization Problem (NOP)

an improved Artificial Bee Colony (ABC) optimization algorithm is proposed in this paper.Firstly

the orthogonal experimental design algorithm was used to generate initial population and discover a new food source for the scout;Secondly

employed bees uses Gaussian Distribution Estimate Algorithm (GDEA) to search

according to fitness value

onlooker bees select one employed bees and search new nectar source in an self-adaptive differential search algorithm.At last this algorithm is tested on 4 standard benchmark functions

and the experimental results show this algorithm has some advantages in convergence velocity

solution precision

and stabilization.