New dispatching rule of LMTT shuttle cars using fuzzy inference and ant colony algorithm

This paper deals with dispatching rule of Linear Motor-based Transfer Technology (LMTT) shuttle cars in port terminal. A novel dispatching method is proposed by using fuzzy inference with Ant Colony algorithm (ACA) which optimizes fuzzy rules. Fuzzy knowledge base which contains data and rule bases is firstly obtained from designed process by genetic approach and then generated rule base is optimally pruned by additional process. The proposed dispatching method is applied to an agile port terminal in California, USA. Simulation result shows that the method determines optimal rules for fuzzy control system and demonstrates an efficient dispatching approach for LMTT shuttle cars comparing typical fuzzy dispatching method.