Simplified Crayfish Optimization Algorithm

A simplified crayfish optimization algorithm is proposed to address the complex form and low operational efficiency of basic crayfish optimization algorithms. Firstly, the position update method of foraging behavior in the basic crayfish optimization algorithm was analyzed. And then a random search radius to optimize the foraging range was used, so as to reduce the process of generating a random number and calculating sine and cosine. Through optimization experiments on 23 universal benchmark test functions, both the simplified algorithm and the basic algorithm underwent 30 operations, and their average, standard deviation, and average running time were compared. The results show that the simplified algorithm fully maintains the basic algorithm’s convergence speed, convergence accuracy, robustness and other performance in finding the optimal solution, and reduces the average running time by 7.63%, improving the running efficiency.