Combinatorial models for optimisation of placement of refuelling stations and routing for alternative fuel vehicles in road network

替代燃料汽车 (AFV)，特别是电动汽车和混合动力汽车，在道路交通网络中发挥着越来越重要的作用。尽管它们有很多优点，但目前它们的使用还存在许多挑战。例如，电动汽车通常具有相对较短的续航里程，需要大量的电池充电时间，并且通常依附于电网的现有容量。一般而言，有限的碳氢化合物资源以及与内燃机使用相关的大规模环境问题激发了人们对开发 AFV 和相应技术的浓厚兴趣。 AFV 背后的主要理念是使其更加节能、环保，并尽可能使用可再生能源。与 AFV 及相应技术相关的问题和挑战包括在何处以及如何为 AFV 提供燃料、如何有效使用它们以及如何公开采用它们。该博士项目的主要目标是开发新的数学模型和组合优化技术，以智能高效地开发道路网络基础设施，以使用新型能源（例如能源）进行车辆导航。电力、生物燃料、氢气，并就现有基础设施的有效路线提供建议。这将基于使用图和有向图开发更微妙的数学模型，并通过算法解决相应的组合优化问题，获得相关的分析和结构结果来完成。我们将使用不同类型的主导集合概念来检查加权图和有向图的新模型，随后开发新的方法以提供高效且有效的算法解决技术。将特别关注将模型扩展到大型道路网络。

Alternative fuel vehicles (AFV's), in particular, electric and hybrid vehicles, play an increasing role in road transport networks. Despite their advantages, currently there are many challenges associated with their usage. For example, electric vehicles usually have a relatively short cruising range, require significant battery charging time, and normally are attached to the existing capacities of the electric grid. In general, a strong interest in development of AFV's and corresponding technologies is motivated by limited resources of hydrocarbons and large-scale environmental issues associated with usage of internal combustion engines. The main ideas behind AFV's are to have them more energy efficient, environmentally friendly and, whenever possible, using renewable energy resources. Problems and challenges associated with AFV's and corresponding technologies include where and how to fuel AFV's, how to use them in an efficient way, and how to make them publicly adopted. The main objective of this PhD project is to develop new mathematical models and combinatorial optimisation techniques for smart and efficient development of road network infrastructure for navigation of vehicles using new types of energies, e.g. electric, biofuel, hydrogen, and to advise on efficient routing with respect to the existing infrastructure. This will be based on development of more subtle mathematical models using graphs and digraphs and done by algorithmically solving the corresponding combinatorial optimisation problems, obtaining related analytical and structural results. We will examine new models on weighted graphs and digraphs using different types of dominating set concepts, subsequently developing new methodologies to provide efficient and effective algorithmic solution techniques. Special attention will be paid to scaling of the models to large-size road networks.