Genetic algorithm solving capacitated automatic guided vehicle system for scheduling problems

In this article, through the in-depth analysis of handling techniques of scrap material in a cigarette factory and working trait of automatic guided vehicle (AGV), and considering the capacitated of AGV transportation, a new scheduling policy is proposed for its transit of the scrap in one manufacture unit, a capacitated GA model is also proposed to solve AGV scheduling problems. Based on self-learning and the improved GA, and considering the compromising solutions for the capacitated of AGV, the real-time scheduling policy of AGV is provided. The rule of encoding, selecting, crossover selection and variation probability is studied. The results of the simulation calculation and application in the cigarette factory have been effectively improved, and the example proves that the research is feasible and effective. © (2012) Trans Tech Publications, Switzerland.