Green railways optimization algorithms

对碳排放、气候变化和可持续性的担忧促使全球努力减少交通系统的能源消耗。降低铁路网能耗是这一努力的重要组成部分和目标。在其他技术创新中，这需要动态实时优化方面的进步。然而，数学优化技术在铁路行业的实际应用并不广泛。该研究项目解决了这一差距，并专注于铁路网络的实时优化，以最大限度地减少能源消耗。在更大的背景下，我们的努力将为实现绿色、灵活的加拿大铁路运输系统铺平道路，该系统可以动态适应不断变化的环境条件，同时共同最大限度地提高能源效率。就其重点而言，我们的项目有可能对加拿大社会和经济产生重大影响，并可以在绿色经济中准备高价值的HQP。

Concerns over carbon emissions, climate change and sustainability are motivating global efforts to reduce energy consumption in transportation systems. Reducing energy consumption in railway networks is an important component and goal of such efforts. This requires, among other technological innovations, advances in dynamic real-time optimization. Yet, real-world applications of mathematical optimization techniques are not widespread in the railway industry. This research project addresses this gap and is focused on real-time optimization of railway networks towards minimizing energy consumption. In the larger context, our efforts will pave the way for realizing green, agile Canadian railway transportation systems that dynamically adapt to changing environmental conditions, while jointly maximizing energy efficiency. By its focus, our project has the potential for significant impact on the Canadian society and economy, and can be prepare highly valuable HQP in a green economy.