Optimisation for Integrated Service Planning and Operation

**目前车队基础设施规划的方法主要集中在类似的车辆更换上（基础设施规划在很大程度上是次要的）。**我们的研究表明，对于客运和车队服务，这种类似的替代方法可能会增加25%的基础设施需求，增加类似数量的总体基础设施成本，增加电网限制的可能性，并推高消费者的成本。为了克服这一挑战，需要同时解决三个关键（但相互关联的）问题，而不是同类方法。我们的解决方案将首次通过构建基于超启发式优化和人工智能的ALM系统和模拟器来共同解决问题。该解决方案将保证最低的“基础设施总成本”，为车队提供关键的成本优势，并为服务用户提供更低的价格。

**Current approaches to fleet infrastructure planning focus predominantly on like-for-like replacement of vehicles (with infrastructure planning largely a second-order concern).** Our research indicates that for passenger and fleets services, this like-for-like replacement approach risks increasing the infrastructure needed by 25%, increasing overall infrastructure costs by a similar amount, increasing the likelihood of grid constraints and pushing up costs for consumers.To overcome this challenge, instead of the like-for-like approach, three critical (but inter-related) problems need to be solved simulateneously. Our solution will solve problems together for the first time by building an ALM system and emulator based on hyperheuristic optimisation and AI.The solution will then guarantee the lowest "total cost of infrastructure", delivering critical cost advantage to fleets and lower prices to service users.