基于历史事件数据的预期时空需求下最优异构搜救资产选址模型

Optimal heterogeneous search and rescue asset location modeling for expected spatiotemporal demands using historic event data

Journal of the Operational Research Society · 2021
被引 11
ABS 3

中文导读

利用7.5年历史事件数据,提出两阶段方法优化美国海岸警卫队异构搜救资产部署,使预期响应时间降低至少9.6%。

Abstract

The United States Coast Guard is charged with coordinating all search and rescue missions in maritime regions within the United States’ purview. Given the size of the Pacific Ocean and limited available resources, the service seeks to posture its fleet of organic assets to reduce the expected response time for such missions. Leveraging 7.5 years of historic event records for the region of interest, we demonstrate a two-stage solution approach. In the first stage, we develop a stochastic zonal distribution model to evaluate spatiotemporal trends for emergency event rates and response strategies. In the second stage, results from the aforementioned analysis enable parameterization of a bi-objective MILP to identify the best locations to station limited heterogeneous search and rescue assets. This research models both 50th and 75th percentile forecast demands across both the set of current homeports, and a larger set of feasible basing locations. Results provide a minimum 9.6% decrease in expected response time over current asset basing. Our analysis also reveals that positioning assets to respond to 75th percentile demands sacrifices, at most, 2.5% in response time during median demand months, whereas positioning for median demand results in operationally inadequate response capability when 75th percentile demands are encountered.

运筹学应急管理海岸警卫搜救选址模型