An Improved Chicken Algorithm Based on Positive Learning and Reverse Learning

A Chicken Swarm Optimization with Positive Learning and Reverse Learning(PRCSO) was proposed to solve the defect that traditional Chicken Swarm Optimization(CSO) is easy to fall into local optimum. The cock crow always learns the optimal particles in each iteration, so that the algorithm can quickly enter the optimal region to find food; and when the algorithm falls into the local optimal solution, Learn to jump out of the local optimal. The results on six typical standard test functions show that the improved CSO not only improves the global search ability, but also the search efficiency, search accuracy and convergence rate are better than the traditional CSO. Especially in dealing with high-dimensional function problems, the improved HJCSO shows a strong advantage.