Using Improved Ant Colony Algorithm to Investigate EMU Circulation Scheduling Problem

Abstract EN

High-speed railway is one of the most important ways to solve the long-standing travel difficulty problem in China.

However, due to the high acquisition and maintenance cost, it is impossible for decision-making departments to purchase enough EMUs to satisfy the explosive travel demand.

Therefore, there is an urgent need to study how to utilize EMU more efficiently and reduce costs in the case of completing a given task in train diagram.

In this paper, an EMU circulation scheduling model is built based on train diagram constraints, maintenance constraints, and so forth; in the model solving process, an improved ACA algorithm has been designed.

A case study is conducted to verify the feasibility of the model.

Moreover, contrast tests have been carried out to compare the efficiency between the improved ACA and the traditional approaches.

The results reveal that improved ACA method can solve the model with less time and the quality of each representative index is much better, which means that efficiency of the improved ACA method is higher and better scheduling scheme can be obtained.