Ant colony optimisation for a resource-constrained shortest path problem with applications in multimodal transport

Multimodal transport provides great flexibility in freight logistics which on the other hand leads to a sophisticated decision problem when choosing shipping options. Advanced analysing and planning tools are desired in supporting the decision making so as to enable the power of multimodal transport. In this paper, features and evolving patterns of a generalised multimodal network derived from industrial applications are analysed. A corresponding routing problem is defined in order to optimise the transportation cost. This problem entails selections on transport modes and paths subject to various kinds of restrictions. We show that the routing problem is a resource constrained shortest path problem and therefore is NP-hard. An ant algorithm is then developed and tested with datasets simulating real scenarios. Experimental results prove the effectiveness of our approach.

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