An Lévy Flight Based Honey Badger Algorithm for Robot Gripper Problem

The honey badger algorithm (HBA) is a recent meta-heuristic optimization algorithm that solves optimization problems by simulating the foraging behavior of honey badgers. To solve the poor convergence of this algorithm in the face of complex optimization problems and to improve the optimization performance of HBA, this paper proposes an enhanced Lévy based HBA algorithm and applies it to the optimization problem of the robot gripper. First, we improve the optimization efficiency of the basic HBA by using the Lévy flight strategy to enhance the local search capability and avoid falling into the local optimum. Secondly, we verify the performance of LHBA by the CEC2020 test function. The experiments show that the LHBA algorithm has good optimization ability. Finally, LHBA is used to solve the robot gripper optimization problem. The results show that LHBA can obtain the minimum value of the difference between the minimum force and the maximum force and successfully solve this optimization problem.