Emergency Railway Transportation Planning Using a Hyper-Heuristic Approach

Abstract

The railway has played a significant role in disaster relief transportation in China. This paper presents an emergency railway transportation problem, which is to use the limited transport capability to meet the urgent relief transportation requirements. We have applied several state-of-the-art evolutionary algorithms to a variety of problem instances, but have found that none of them can obtain satisfactory solutions in all cases. To overcome this obstacle, we integrate a set of individual heuristic operators into a hyperheuristic framework, which performs a stochastic search on the low-level heuristics by using feedback on their performance in the process of problem solving, thus yielding a high overall performance on different instances. Computational experiments show that the hyperheuristic exhibits significant advantages over the individual heuristics. The problem model and the hyperheuristic solution approach have also been successfully applied to the emergency railway transportation during the 2013 Dingxi earthquake, in China.

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