A review on metaheuristic algorithms of Ant colony, Genetic and Particle swarm in robot’s routing

In this Research using four important metaheuristic methods of optimization including Ant colony, particle swarm, genetic and metal cooling simulation, robot’s motion route has been investigated. Metaheuristic optimization methods are smart and considerably are very powerful in finding high quality answers in complicated problems. Here in, four methods such as ant colony, particle swarm and genetic algorithm are used for robot’s movement routing instead of other old methods. First the problem is examined, the current location (origin) and robot’s destination are studied, as well as location of the obstacles in the robot. Afterwards, in order to explain the machanisms of the four aforementioned algorithms and to understand the differences and similarities and also to develop them, optimizing the robot's movement routing is taken into consideration.

Keywords:

Metaheuristic algorithm , Ant colony algorithm , particle swarm algorithm , Genetic algorithm , Robot routing.