Abstract
This work shows a review about the multimodal transport network problem. This kind of problem has been studied for several researchers who look for solutions to the large numbers of problems relating on the transport systems like: traffic jam, pollution, delays, among others. In this work are presented a standard mathematical formulation for this problem and some other variations, which make the problem more complex and harder to be solved. There are many approaches to solve it that are found in the literature and they are divided according to classical methods and soft computing methodologies, which combine approximate reasoning as fuzzy logic and functional as metaheuristics and neural networks. Each approach has its advantages and disadvantages that are also shown. A novel approach to solve the multimodal transport network problem in fuzzy environment is developed and this approach is also applied in a theoretical problem to illustrate its effectiveness.
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The authors want to thank the Brazilian agencies CAPES and FAPESP with project number 2010/51069-2.
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Verga, J., Silva, R.C., Yamakami, A. (2018). Multimodal Transport Network Problem: Classical and Innovative Approaches. In: Cruz Corona, C. (eds) Soft Computing for Sustainability Science. Studies in Fuzziness and Soft Computing, vol 358. Springer, Cham. https://doi.org/10.1007/978-3-319-62359-7_14
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