Temperature Determination in Simulated Annealing Using Learning Automata

摘要

This paper presents a new method for temperature parameter determination in simulated annealing for escaping local minimum in artificial potential fields. Learning automata for determine parameter is used. Temperature parameter determination cause improving to escape local minimum, high temperature cause robot farther as obstacles and long path. Furthermore, choice low temperature cause robot can't escape local minimum. The simulation results reflects that how the work has improved path and determine temperature.