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首页> 外文会议>World environmental and water resources congress >Integrating an agent-based model with a multi-objective evolutionary algorithm to warn consumers in a water contamination event using emergency vehicles
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Integrating an agent-based model with a multi-objective evolutionary algorithm to warn consumers in a water contamination event using emergency vehicles

机译：将基于主体的模型与多目标进化算法相集成，以在使用应急车辆的水污染事件中向消费者发出警告

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Many protective response actions are available to protect consumers affected by a water distribution contamination event. Routing a fleet of emergency vehicles to disseminate water warnings is considered in this study. Identifying optimal trips to effectively notice consumers is difficult as a water contamination event is a complex and dynamic system and vehicle routing problems are categorized as NP-hard domain. A novel framework is developed by coupling an agent-based model with an optimization algorithm to search for optimality in a warning dissemination. Solutions representing an optimal front are explored to demonstrate the relationship between the number of exposed consumers and the maximum travel time as conflicting objectives. NSGA-Ⅱ is used with a tree-based representation. The developed framework is applied to a virtual case study, Mesopolis.
机译：许多保护性响应措施可用来保护受配水污染事件影响的消费者。在这项研究中，考虑安排应急车队分发水警告。由于水污染事件是一个复杂而动态的系统，因此很难确定最佳行程来有效地吸引消费者，因为这是一个复杂且动态的系统，并且车辆路线选择问题被归类为NP硬域。通过将基于代理的模型与优化算法耦合在一起以搜索预警分发中的最优性，从而开发出一种新颖的框架。探索了代表最佳前沿的解决方案，以证明暴露的消费者数量与最长旅行时间之间的关系作为矛盾的目标。 NSGA-Ⅱ与基于树的表示一起使用。所开发的框架将应用于虚拟案例研究Mesopolis。

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