Wild Geese Migration Optimization Algorithm: A New Meta-Heuristic Algorithm for Solving Inverse Kinematics of Robot.

This paper proposes a new meta-heuristic algorithm, named wild geese migration optimization (GMO) algorithm. It is inspired by the social behavior of wild geese swarming in nature. They maintain a special formation for long-distance migration in small groups for survival and reproduction. The mathematical model is established based on these social behaviors to solve optimization problems. Meanwhile, the performance of the GMO algorithm is tested on the stable benchmark function of CEC2017, and its potential for dealing with practical problems is studied in five engineering design problems and the inverse kinematics solution of robot. The test results show that the GMO algorithm has excellent computational performance compared to other algorithms. The practical application results show that the GMO algorithm has strong applicability, more accurate optimization results, and more competitiveness in challenging problems with unknown search space, compared with well-known algorithms in the literature. The proposal of GMO algorithm enriches the team of swarm intelligence optimization algorithms and also provides a new solution for solving engineering design problems and inverse kinematics of robots.

Study on the Mechanical Properties of Monocrystalline Germanium Crystal Planes Based on Molecular Dynamics.

Nanoindentation and atomistic molecular dynamics simulations of the loading surface of monocrystalline germanium were used to investigate the evolution of the key structure, the force model, the temperature, the potential, and the deformable layer thickness. The mechanical characteristics of typical crystal planes (001), (110), and (111) of the crystal system were compared under load. It was observed that the hardness and stiffness of the (110) plane were greatest among the three crystal planes, whereas the hardness and stiffness of the (111) plane were lowest. Moreover, the deformation layers at the ends of both planes were basically flat. The processing efficiency of the (111) surface was higher; thus, the (111) surface was considered the best loading surface. It was concluded that the subsurface defects of the monocrystalline germanium (111) plane were smaller and the work efficiency was higher during the processing of monocrystalline germanium, making it ideal for monocrystalline germanium ultra-precision processing.