Human-Computer Optimisation for Water Systems Planning and Management (HOWS)

人们普遍承认，社区健康、经济和环境可持续性所依赖的水和废水基础设施资产在全球范围内资金严重不足。例如，美国环保局发现了近550亿美元的资金缺口(美国环境保护协会，2011年)。在英格兰和威尔士，水务公用事业资产的总估计资本价值为2548亿GB(水务办公室，2015年)，但在2010至2015年间，仅分配了129亿GB用于维护和更换资产。再加上降低客户账单的努力，水务公司将面临更大的压力，需要找到方法弥合可用资金和所需资金之间的差距。因此，优化方法在这一领域得到了广泛的研究和应用就不足为奇了(Maier等人，2014)。这些方法无法在优化中包含“不可量化的”或难以量化的内容，但重要的考虑因素，如用户主观领域知识，导致了水行业对优化的采用有限。许多认知和计算挑战伴随着涉及复杂工程系统的设计、规划和管理。水工业基础设施资产(即水分配和废水网络)是系统的例子，由于其规模、概念和计算的复杂性、非线性行为以及通常是离散/组合的性质，这些系统对完全自动化的优化方法构成了严重困难。Goulter(1992)首先阐述了这些困难，他主要将供水管网(WDN)设计中缺乏应用优化的原因归因于缺乏合适的专业软件。尽管此类软件现已广泛使用(例如InfoWorks、Water Gems、EPANET等)，但由于缺乏用户对功能、假设和限制的理解，仍限制了实践工程师使用优化(Walski，2001)。需要纯粹定量数学表示的自动化方法不利用人类的专业知识，只能找到关于总是过于简化的问题表述的最优解决方案。过去在这一领域的研究重点几乎完全集中在算法问题上。然而，这种方法忽略了许多重要的人机交互问题，必须解决这些问题，以便为从业者提供工程上直观的、实用的优化问题解决方案。该项目将通过创建一种视觉分析优化方法，将人类的专业知识(通过“人在循环”的交互优化)、IT基础设施(云/并行计算)和最先进的优化技术整合在一起，为水务行业开发高度优化的、工程上直观的解决方案，从而加深对如何改进复杂水系统的工程设计、规划和管理的新理解。新方法将在英国水务行业提供的问题上进行广泛测试，并将涉及这一重要问题领域的实践工程师和专家。

It is widely acknowledged that the water and wastewater infrastructure assets, which communities rely upon for health, economy and environmental sustainability, are severely underfunded on a global scale. For example, a funding gap of nearly $55 billion has been identified by the US EPA (ASCE, 2011). In England and Wales, the total estimated capital value of water utility assets is £254.8 billion (Ofwat, 2015), but between 2010 and 2015 only £12.9 billion was allocated for maintaining and replacing assets. Combined with the drive to reduce customers' bills, there will be even more pressure on water companies to find ways to bridge the gap between the available and required finances. As a result of this it is not surprising that optimisation methods have been extensively researched and applied in this area (Maier et al., 2014).The inability of those methods to include into optimisation 'unquantifiable' or difficult to quantify, yet important considerations, such as user subjective domain knowledge, has contributed to the limited adoption of optimisation in the water industry. Many cognitive and computational challenges accompany the design, planning and management involving complex engineered systems. Water industry infrastructure assets (i.e., water distribution and wastewater networks) are examples of systems that pose severe difficulties to completely automated optimisation methods due to their size, conceptual and computational complexity, non-linear behaviour and often discrete/combinatorial nature. These difficulties have first been articulated by Goulter (1992), who primarily attributed the lack of application of optimisation in water distribution network (WDN) design to the absence of suitable professional software. Although such software is now widely available (e.g., InfoWorks, WaterGems, EPANET, etc.), the lack of user under-standing of capabilities, assumptions and limitations still restricts the use of optimisation by practicing engineers (Walski, 2001). Automatic methods that require a purely quantitative mathematical representation do not leverage human expertise and can only find solutions that are optimal with regard to an invariably over-simplified problem formulation. The focus of the past research in this area has almost exclusively been on algorithmic issues. However, this approach neglects many important human-computer interaction issues that must be addressed to provide practitioners with engineering-intuitive, practical solutions to optimisation problems. This project will develop new understanding of how engineering design, planning and management of complex water systems can be improved by creating a visual analytics optimisation approach that will integrate human expertise (through 'human in the loop' interactive optimisation), IT infrastructure (cloud/parallel computing) and state-of-the-art optimisation techniques to develop highly optimal, engineering intuitive solutions for the water industry.The new approach will be extensively tested on problems provided by the UK water industry and will involve practicing engineers and experts in this important problem domain.