Dynamic Multi-objective Optimization Problem of Container Intermodal Transport: An Empirical Analysis on the Belt and Road Initiative of China

Abstract

The Belt and Road Initiative of China proposes a higher request for the development of container intermodal transport. The traditional intermodal transport organization mode may change: the daily handling capacity of container railway central terminal will increase, speed of train will improve, there will be more and more double-stack container train come into use. These changes will have far-reaching consequences on the container multimodal transport development of China. This paper attempts to evaluate the economic and environmental effect on the potential change of container intermodal transport of China on the Belt and Road Initiative, with a specific focus on energy consumption and emission. Multi-objective optimization model is built to minimize transport time, cost, energy consumption, and also emissions, which is based on simulation model of locomotive, Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is used to solve the multi-objective optimization model. An empirical case regarding container intermodal transport from Shanghai to Urumqi is applied to verify the validity of model in the end. The dynamic multi-objective optimization model allows the logistics enterprise to be more flexible in their decision to plan the scheme of container intermodal transport.