Multicriteria search with multiple searchers in uncertain environments

不确定环境下多个搜索者的多标准搜索

• 批准号: 300890-2009
• 负责人: AbiZeid, Irène
• 金额: $ 1.46万
• 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: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=526134
• 关键词: Multicriteria; search; multiple; searchers; uncertain

Search and Rescue (SAR) is one of the greatest humanitarian activities. It comprises the search for, and provision of aid to, persons, ships or other craft which are, or are feared to be, in distress or imminent danger. The objective of SAR is to locate and rescue survivors involved in a SAR incident. Search planning is a particularly important phase, especially when the location of the incident is unknown. Search planning may be seen as the optimal allocation of the available search resources. In this project, we propose to conduct research to develop algorithms for the multiple searchers problem in a multi-criteria context. The objective is to generate, in a reasonable time, near optimal operationally feasible plans for searches conducted in open and vast spaces. We will pay particular attention to uncertainty in detection capabilities, possibility of false alarms, presence of false targets and uncertainty on visibility parameters. The mathematical framework that we will use includes constraint programming, stochastic processes, multi-criteria mathematical programming, meta-heuristics, geographic terrain analysis, and simulation models. Our long term goal is to leverage this research effort with other research funding sources to develop a geographic decision support system prototype that implements multi-criteria evaluation and optimization algorithms based on terrain constraints, physical constraints, time constraints, detection capabilities, type of resources available, etc., and that takes into account the various uncertainties associated with SAR missions. This is in continuance with our past and current research in the area of search planning and decision support for Search and Rescue. The potential benefits are for the SAR organization in general, and for the Canadian public in particular. In an operational context, our research may translate into an increase in the chances of finding survivors, resulting in more saved lives. Another benefit is a potential decrease in the operations costs.

搜索与救援 (SAR) 是最伟大的人道主义活动之一。它包括搜寻陷入或担心陷入困境或迫在眉睫危险的人员、船舶或其他船只并向其提供援助。搜寻与援救的目标是寻找并营救参与搜寻与援救事件的幸存者。搜索计划是一个特别重要的阶段，尤其是当事件发生地点未知时。搜索计划可以被视为可用搜索资源的最佳分配。在这个项目中，我们建议进行研究，开发多标准上下文中多个搜索者问题的算法。目标是在合理的时间内为在开放和广阔空间中进行的搜索生成近乎最佳的操作可行的计划。我们将特别关注探测能力的不确定性、误报的可能性、虚假目标的存在以及能见度参数的不确定性。我们将使用的数学框架包括约束规划、随机过程、多标准数学规划、元启发式、地理地形分析和模拟模型。我们的长期目标是利用这项研究工作与其他研究资金来源，开发一个地理决策支持系统原型，该原型基于地形约束、物理约束、时间约束、探测能力、可用资源类型等实施多标准评估和优化算法，并考虑到与SAR任务相关的各种不确定性。这与我们过去和当前在搜索规划和搜索救援决策支持领域的研究是延续的。潜在的好处是对整个搜寻与援救组织，特别是对加拿大公众而言。在实际操作中，我们的研究可能会增加找到幸存者的机会，从而挽救更多生命。另一个好处是运营成本的潜在降低。