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Cooperative Multiple Agent-Based Algorithm for Evacuation Planning for Victims with Different Urgencies

机译:基于协作多主体的紧急情况下人员的疏散计划算法

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A well-organized evacuation plan is crucial to save more lives in the aftermath of natural disasters. In this paper, a mathematical model and an efficient solution approach are proposed for optimal planning of a fleet of aerial vehicles to save victims with different levels of urgency. Evacuation planning is a task assignment problem combined with scheduling of aerial vehicles with different capabilities while considering complex conditions such as multiple bases for the vehicles, victims with different urgency levels at multiple locations, and multiple safe locations (for example, hospitals and refuges). In our previous work, the problem was formulated as integer linear programming to provide optimal solution. Because the integer linear programming, however, is intractable for a large-scale disaster problem, a heuristic method called the cooperative multiagent-based algorithm is proposed to solve the large-scale problem in practical time. The proposed algorithm defines simple rules for vehicle agents and demand agents (victims), and it applies cooperative interaction between agents to efficiently find a suboptimal solution. The computational efficiency and the performance of the algorithm are demonstrated using illustrative numerical examples based on realistic data.
机译:井井有条的疏散计划对于在自然灾害后挽救更多生命至关重要。在本文中,提出了一种数学模型和一种有效的求解方法,以优化航空器机群的计划,以挽救具有不同紧急程度的受害者。疏散计划是一项任务分配问题,与调度具有不同能力的飞行器相结合,同时考虑了复杂的条件,例如车辆的多个基地,在多个地点具有不同紧急程度的受害者以及多个安全地点(例如,医院和避难所)。在我们以前的工作中,该问题被表述为整数线性规划以提供最佳解决方案。然而,由于整数线性规划对于大规模灾难问题是棘手的,因此提出了一种基于协作多代理的启发式方法,以在实际时间内解决大规模问题。所提出的算法为车辆代理人和需求代理人(受害者)定义了简单的规则,并在代理人之间应用协作交互以有效地找到次优解决方案。使用基于实际数据的说明性数值示例,演示了算法的计算效率和性能。

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