Abstract:Considering the layout characteristics of general industrial enterprise freight transport railway lines (both layout with radial and tree branch), an intelligent optimization method is presented. This method is built on the basis of the placing-in and taking-out operation model, and then, the problem is decomposed into several small scale sub-problems. Furthermore, a two-level optimization strategy is proposed by parallel solving the optimization sub-problems inside the shops with tree branch lines, then solving the optimization problems between the shops in radial line. According to the optimization strategy, a hybrid genetic elite ant colony algorithm is designed for the placing-in and taking-out operation optimization problem. Simulation results prove that the proposed method can effectively optimize the railway placing-in and taking-out operation problem.

Abstract:Placing-in and taking-out operation is an important part of enterprise railway freight transport scheduling. In order to reduce remain time in industrial enterprise freight transport station, and improve the efficiency of train operation, reasonable order of placing-in and taking-out operation is necessary. Considering layout characteristics of general industrial enterprise freight transport rail lines (both layout with radial and tree branch), in this paper, an intelligent optimization method is presented. The method is built based on placing-in and taking-out operation model, and then, the problem is decomposed into several small-scale sub-problems. Furthermore, a two-level optimization strategy is proposed by parallel solving the optimization sub-problems inside the shops with tree branch lines, then solving the optimization problems between the shops in radial line. According to the optimization strategy, a hybrid genetic elite ant colony algorithm is designed for placing-in and taking-out operation optimization problem. Simulation results prove that the proposed method can effectively optimize the railway placing-in and taking-out operation problem.