Selective Survey: Most Efficient Models and Solvers for Integrative Multimodal Transport

TL;DR

This paper provides a selective survey of the most efficient models and solvers for multimodal transport systems within Intelligent Transportation Systems, highlighting current methods, industry needs, and research gaps to guide future advancements.

Contribution

It offers a comprehensive overview of existing research, methods, and solvers in multimodal transportation, identifying gaps between theory and real-world applications.

Findings

Identifies key methods and solvers used in multimodal transport optimization.

Highlights industry needs and research gaps in ITS.

Provides a framework for future research directions.

Abstract

In the family of Intelligent Transportation Systems (ITS), Multimodal Transport Systems (MMTS) have placed themselves as a mainstream transportation mean of our time as a feasible integrative transportation process. The Global Economy progressed with the help of transportation. The volume of goods and distances covered have doubled in the last ten years, so there is a high demand of an optimized transportation, fast but with low costs, saving resources but also safe, with low or zero emissions. Thus, it is important to have an overview of existing research in this field, to know what was already done and what is to be studied next. The main objective is to explore a beneficent selection of the existing research, methods and information in the field of multimodal transportation research, to identify industry needs and gaps in research and provide context for future research. The selective survey covers multimodal transport design and optimization in terms of: cost, time, and network topology. The multimodal transport theoretical aspects, context and resources are also covering various aspects. The survey's selection includes nowadays best methods and solvers for Intelligent Transportation Systems (ITS). The gap between theory and real-world applications should be further solved in order to optimize the global multimodal transportation system.