Driving Efficiency in Same-Day E-Cargo Bike Logistics: Dynamic Dispatch Automation via LLMs

提高当日电动货运自行车物流的效率：通过法学硕士实现动态调度自动化

• 批准号: 10081138
• 金额: $ 6.35万
• 依托单位: KALE COLLECTIVE LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10081138
• 关键词: Driving; Efficiency; Same; Day; Cargo

Our project aims to revolutionise same-day e-cargo bike logistics in London through the innovative application of Large Language Models (LLMs). We intend to fundamentally transform how e-cargo bike operators integrate unpredictable same-day demand with pre-planned delivery flows, a challenging aspect that significantly affects efficiency and productivity.By employing LLMs, we aim to process extensive historical and real-time data, predict immediate demand accurately, and enable dynamic dispatch operations that are both efficient and intuitive. This way, we can weave uncertain same-day demand into already planned delivery flows without disrupting the system. The LLMs serve as a conversational interface, allowing dispatchers to define constraints and optimisation objectives in a more straightforward manner, significantly simplifying traditionally cumbersome manual interactions.Our project thrives on the collaboration with a leading e-cargo bike operator in London, a partnership that blends hands-on industry experience with our AI and ML expertise. Together, we're pursuing substantial productivity gains and efficiency improvements for same-day delivery services, a sector ready for disruption.The environmental implications of our project are noteworthy. By enhancing the operational efficiency and competitiveness of e-cargo bikes, we're championing a more sustainable alternative to traditional delivery vans. This stands in alignment with the larger goal of decarbonising urban transport, significantly contributing to the fight against climate change.By bridging technology and sustainability, our project stands at the forefront of urban logistics innovation. We're embarking on an ambitious journey to transform urban deliveries, empowered by AI leading technologies, making them efficient, profitable, and environmentally friendly while catering to the growing demand for immediate delivery services.

我们的项目旨在通过大型语言模型（llm）的创新应用，彻底改变伦敦当日电子货运自行车物流。我们打算从根本上改变电动货运自行车运营商将不可预测的当日需求与预先计划的交付流程相结合的方式，这是一个具有挑战性的方面，会显著影响效率和生产力。通过使用法学硕士，我们的目标是处理广泛的历史和实时数据，准确预测即时需求，并实现高效和直观的动态调度操作。这样，我们就可以在不破坏系统的情况下，将不确定的当日需求编织到已经计划好的交付流中。llm作为一个会话接口，允许调度程序以更直接的方式定义约束和优化目标，大大简化了传统上繁琐的手动交互。我们的项目在与伦敦一家领先的电动货运自行车运营商的合作中蓬勃发展，这种合作将实践行业经验与我们的人工智能和机器学习专业知识相结合。我们正在共同努力，大幅提高当日送达服务的生产率和效率，这是一个随时可能被颠覆的行业。我们项目的环境影响是值得注意的。通过提高电动货运自行车的运营效率和竞争力，我们正在倡导一种比传统货车更可持续的替代方案。这与城市交通脱碳的更大目标是一致的，为应对气候变化做出了重大贡献。通过连接技术和可持续性，我们的项目站在城市物流创新的最前沿。我们正在开展一项雄心勃勃的旅程，以人工智能领先技术为动力，改变城市配送，使其高效、盈利和环保，同时满足对即时配送服务日益增长的需求。