Comparing of Routine Nano-particles for Creating Pattern Using Genetic Algorithm and Particle Swarm Optimization - Ant System in Simulation using Atomic Force Microscopy

Pattern creating with nano-particle is one of the best application methods in nano-scale that it will be used for new pattern creating and make micro/nano-electromechanical System (MEMS/NEMS) in future. Particle swarm optimization algorithm is one of evolutionary computation techniques and the optimization method based on population and ant algorithm, optimization algorithm is modeled based on ants. In addition explained algorithms, the genetic algorithm is adaptive methods that use to optimizing of problem. In this paper, we have created modified and combined of particle swarm optimization and genetic algorithm. Also this method has been implemented using modified in genetic algorithm. In other words, proposed algorithms have been implemented with modified in their structures and considering applied condition for creating of pattern with nano-particles. Dynamic modeling and simulation for manipulating of cantilever and probe in the liquid and vacuum environment in Mathimatica Software done. Routing of algorithms implemented in Matlab Software. The functionality of the method are: Firstly, the result is minimum of time and energy in moving of cantilever. In fact we can find the minimum of routing. Secondly, during the transport of nano-particles mustn’t occur any collision, because in this case the atomic force microscope has to scan the surface again, and it will take more time. So we will get the minimum time for creating of the special pattern without any collision using the proposed algorithms.