Artificial Intelligence meets Multi-Criteria Decision Aiding in smart sustainble cities

人工智能在可持续智慧城市中满足多标准决策辅助

• 批准号: RGPIN-2020-05642
• 负责人: AbiZeid, Irène
• 金额: $ 1.89万
• 依托单位: Université Laval
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=717722
• 关键词: Artificial; Intelligence; meets; Multi; Criteria

In today's organizations, transparency and accountability are increasingly required, especially for decisions involving environmental and public resources, which have an impact on groups with diverse vulnerability levels and conflicting interests. This is particularly true when it comes to city planning and management where issues with drinking water source protection, wastewater management, transportation planning, social housing planning or street rehabilitation must be addressed in a context of increasing awareness of social inequities and environmental degradation related to anthropogenic activities, and in an era of social media, citizens participation and big data. This context has led, in the mid 2010s, to the emergence of the concept of smart sustainable cities, i.e. cities which, "supported by information and communications technologies (ICT) and aware of local or environmental limitations, meet the needs of their current inhabitants without compromising the ability of other people or other generations to meet their needs" (Höjer & Wangel, 2015). But how can a city evolve toward a smart sustainable city? How can public decision processes be conducted to ensure sustainable, robust, rigorous, inclusive, transparent, acceptable and fair decisions while taking advantage of the ICT infrastructure? The answer is interdisciplinary and lies partly in the field of Analytics, more precisely in participatory multicriteria decision aiding (MCDA), a sub-discipline of operations research, which has gained an increasing momentum over the last five decades, and in its combination with techniques from Artificial Intelligence, Problem Structuring Methods, Geographic Information Systems, and Preference Learning as they pertain to MCDA decision processes. In this research program, we will design a spatial MCDA framework and develop, validate and evaluate tools to support the MCDA process in relation to the following questions with applications related to smart sustainable cities: 1) What are the environmental characteristics, activities, factors and main difficulties that significantly influence the conduct of a MCDA process and how to deal with them? 2) How can the preferences of all stakeholders be captured and taken into account? 3) How can massive amount of quantitative and qualitative information, sometimes called big data, be integrated in the process? 4) How to evaluate the quality of a MCDA process? 5) How to explain and argue the decision process and the results to the stakeholders to ensure acceptability? Our research program will be conducted following a Design Science orientation. Our theoretical framework will be interdisciplinary and the underpinning philosophical paradigm is critical realism, a philosophy that is consistent with our multimethodological approach. We will apply and test our framework and tools in the following application domains: municipal asset management, drinking water source protection and social housing planning.

在当今的组织中，透明度和问责制的要求越来越高，特别是涉及环境和公共资源的决策，这些决策对具有不同脆弱性水平和利益冲突的群体产生影响。在城市规划和管理方面尤其如此，在社会媒体、公民参与和大数据时代，必须在人们日益认识到与人类活动相关的社会不平等和环境退化的背景下，解决饮用水源保护、废水管理、交通规划、社会住房规划或街道重建等问题。这种背景导致了 2010 年代中期智能可持续城市概念的出现，即“在信息和通信技术 (ICT) 的支持下，并意识到当地或环境限制，满足当前居民的需求，而不损害其他人或其他几代人满足其需求的能力”的城市（Höjer 和 Wangel，2015）。 但城市如何才能发展成为可持续智慧城市呢？如何进行公共决策过程，以确保可持续、稳健、严格、包容、透明、可接受和公平的决策，同时利用信息通信技术基础设施？答案是跨学科的，部分在于分析领域，更准确地说，在于参与式多标准决策辅助（MCDA），它是运筹学的一个子学科，在过去的五年里获得了不断增长的势头，并且与人工智能、问题结构方法、地理信息系统和偏好学习技术相结合，因为它们与MCDA决策过程有关。在本研究项目中，我们将设计一个空间 MCDA 框架，并开发、验证和评估工具来支持 MCDA 流程，解决以下与智慧可持续城市相关的应用问题： 1) 显着影响MCDA过程进行的环境特征、活动、因素和主要困难是什么以及如何处理？ 2) 如何捕捉并考虑所有利益相关者的偏好？ 3）如何在这个过程中整合大量的定量和定性信息（有时称为大数据）？ 4）如何评价MCDA过程的质量？ 5）如何向利益相关者解释和论证决策过程和结果以确保可接受性？ 我们的研究计划将按照设计科学方向进行。我们的理论框架将是跨学科的，其基础哲学范式是批判现实主义，这是一种与我们的多方法论方法一致的哲学。我们将在以下应用领域应用和测试我们的框架和工具：市政资产管理、饮用水源保护和社会住房规划。