In view of falsely high costs

low transportation efficiency and low vehicle utilization caused by manual dispatch of transportation in the process of order delivery and returning of existing foundry enterprises

the order dispatch of foundry enterprises was investigated. A mathematical model of multi-target order dispatch and return transportation with transportation cost

delivery date

and vehicle utilization as indicators was established. A double evolutionary elimination system of teaching and learning algorithm（Diverse poor and rich algorithm-Teaching and learning algorithm

DP-TLBO） was proposed

and a continuous coding method was designed. The reverse learning of the sine acceleration factor was introduced to enhance the local search ability and prevent from falling into the local optimum in the later stage of the search. The dual evolution mechanism of teaching and learning algorithms as well as rich and poor optimization algorithms was adopted to compete and eliminate scheduling schemes. The results of experiments with multiple test functions indicate that the double-evolution elimination teaching and learning algorithm has desirable performance. Finally

the results of multiple scale simulation experiments for two different casting companies reveal that the mathematical model and algorithm proposed lead to the lower costs

higher transportation efficiency and higher vehicle utilization compared with manual transportation methods.