Scheduling and coordinating ongoing asset maintenance projects

维护公共基础设施，如道路、下水道系统和交通系统，对任何市政当局来说都是一项持续的、昂贵的开支。同样，在对加拿大重要的领域（例如采矿）的大型资本密集型公司也面临着维护其设备的挑战。Riva Modeling是这个提议中的工业合作伙伴，它销售的软件允许这些组织在100年的时间框架内为不同类别的资产创建维护计划。在这个项目中，我们将处理大型组织经常管理许多同时进行和相互竞争的维护项目的现实。例如，一个城市可能需要在道路、下水道和城市森林的持续维护之间取得平衡。使用Riva现有软件的输出，我们将调查在10年时间框架内安排资产维护项目的问题，当项目竞争相同的预算，相同的资源（例如，劳动力）和相同的风险限制时。使用真实数据，我们将使用不同的技术（混合整数规划、约束规划、约束整数规划、启发式）开发和经验比较一些数学规划模型，并开发原型软件，与Riva现有的软件集成和补充。该原型将自动将维护项目计划集和一些公司数据转换为数学规划模型，然后进行求解，在平衡年度成本、资源使用和风险的同时提供最佳时间表。

The maintenance of public infrastructure such as roads, sewer systems, and transit systems is an ongoing, costly expense for any municipality. Similarly large capital intensive corporations in areas important to Canada (e.g., mining) are faced with the challenge of maintaining their equipment. Riva Modeling, the industrial partner in this proposal, markets software that allows such organizations to create maintenance plans for their different classes of assets over a 100 year time-frame. In this project, we will address the reality that large organizations often manage many simultaneous and competing maintenance projects. For example, a city may need to balance among ongoing maintenance on roads, sewers, and the urban forest. Using the output from Riva's existing software, we will investigate the problem of scheduling asset maintenance projects over a 10 year time-frame when the projects compete for the same budget, the same resources (e.g., labour force), and the same risk limitations. Using real data, we will develop and empirically compare a number of mathematical programming models using different technology (mixed integer programming, constraint programming, constraint integer programming, heuristics) and develop prototype software that will integrate with and complement Riva's existing software. This prototype will automatically transform the set of maintenance project plans plus some company data into a mathematical programming model that will then be solved, providing an optimal schedule while balancing annuals costs, resource usage, and risk.