摘要：This post will introduce the extensive application of emergency systems (2) of the journal article "Improving emergency responsive
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今天小编为大家带来“越览（109）——精读期刊论文
《Improving emergency responsiveness with
management science》的
5应急系统的大量应用（2）”。
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Dear, this is LearningYard Academy!
Today, the editor brings you the
＂Yue Lan (109)：Intensive reading of the journal article＇Improving emergency responsiveness with
management science:
5 Extensive application of emergency systems (2)＇＂.
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一、内容摘要（Summary of content）
本期推文将从思维导图、精读内容、知识补充三个方面介绍期刊论文《Improving emergency responsiveness with management science》的应急系统的大量应用（2）。
This post will introduce the extensive application of emergency systems (2) of the journal article "Improving emergency responsiveness with management science" from three aspects: mind mapping, intensive reading content, and knowledge supplement.
二、思维导图（Mind mapping）
三、精读内容（Intensive reading content）
本段介绍了巡逻车分配模型（PCAM）模型在处理多车调度中的不足，以及Linda Green与Peter Kolesar合作开发的多车调度（MCD）排队模型。MCD模型通过引入多服务器、多优先级机制，更精准地模拟多车服务需求，解决了PCAM对延迟预测不准确的问题。
This section introduces the shortcomings of the patrol car assignment model (PCAM) model in dealing with multi-car dispatch, and the multi-car dispatch (MCD) queuing model developed by Linda Green and Peter Kolesar. The MCD model introduces a multi-server and multi-priority mechanism to more accurately simulate the service needs of multiple vehicles, solving the problem of inaccurate delay prediction of PCAM.
接着MCD模型在纽约市验证后纳入PCAM修订版，广泛推广并用于城市警消合并与单警巡逻系统研究。尽管研究表明单警系统需增加巡逻车保障效率与安全，市长办公室强推计划引发争议，导致支付纠纷和研究人员被列入黑名单。最终，单警巡逻在有限范围内实施。
The MCD model was then validated in New York City and incorporated into the revised version of PCAM, which was widely promoted and used in the study of the city's police-fire merger and single-police patrol system. Although research showed that the single-police system needed to increase patrol cars to ensure efficiency and safety, the mayor's office pushed the plan, which caused controversy, resulting in payment disputes and researchers being blacklisted. In the end, single-police patrols were implemented on a limited scale.
最后作者提到Chelst (1981) 比较单警与双警巡逻系统效率，明确单警巡逻的优势。2003年，他帮助布法罗市评估并实施单警巡逻，显著提升了响应时间。
Finally, the author mentioned that Chelst (1981) compared the efficiency of single-police and double-police patrol systems and clarified the advantages of single-police patrol. In 2003, he helped the city of Buffalo evaluate and implement single-police patrol, which significantly improved response time.
四、知识补充（Knowledge supplement）
多车调度排队模型（MCD）是一种用于分析和优化多服务器系统的排队模型，特别适用于需要多个服务单元（如巡逻车、急救车辆）协同完成任务的场景。以下是其核心特点：
The Multi-Car Dispatch (MCD) model is a queuing model used to analyze and optimize multi-server systems. It is particularly suitable for scenarios where multiple service units (such as patrol cars and emergency vehicles) need to work together to complete tasks. The following are its core features:
1. 多服务器：模型支持多个服务单元，适合处理多车调度需求。
1. Multi-server: The model supports multiple service units and is suitable for handling multi-vehicle dispatching requirements.
2. 随机需求：每项任务所需的服务单元数量是随机的，由概率分布描述。
2. random demand: The number of service units required for each task is random and described by a probability distribution.
3. 优先级机制：模型支持任务的优先级划分，高优先级任务可以优先分配资源。
3. Priority mechanism: The model supports task priority division, and high-priority tasks can be allocated resources first.
4. 服务规则：服务只有在满足最低服务单元要求时才会开始，实际使用的单元数量取决于可用资源。
4. Service rules: Service will only start when the minimum service unit requirements are met, and the actual number of units used depends on the available resources.
5. 性能指标：模型可以计算延迟概率、平均延迟时间以及各优先级任务的资源使用情况。
5. Performance indicators: The model can calculate the delay probability, average delay time, and resource usage of each priority task.
MCD模型通过引入多服务器、多优先级和随机需求等复杂特性，有效解决了传统排队模型无法处理的多车调度问题，是应急管理和服务系统优化的重要工具。
The MCD model effectively solves the multi-vehicle scheduling problem that traditional queuing models cannot handle by introducing complex features such as multiple servers, multiple priorities, and random demands. It is an important tool for emergency management and service system optimization.
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参考文献：Linda V. Green, Peter J. Kolesar. Improving Emergency Responsiveness with Management Science [J]. Management Science, 2004, 50(8): 1001-1014.
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