Optimizing Security Patrolling Strategies: A Cross-Domain Review of Mathematical Models and Applications
暫譯: 優化安全巡邏策略：數學模型與應用的跨領域回顧

Tokel, Yusuf Ihsan, Zhuang, Jun

Optimizing Security Patrolling Strategies: A Cross-Domain Review of Mathematical Models and Applications
  • 出版商: Springer
  • 出版日期: 2026-01-03
  • 售價: $2,080
  • 貴賓價: 9.5 折 $1,976
  • 語言: 英文
  • 頁數: 66
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3032026164
  • ISBN-13: 9783032026163
  • 相關分類: 機率統計學 Probability-and-statistics

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

This book presents a comprehensive examination of crime patrolling problems across various domains, including robotics, security, and law enforcement, with a focus on the mathematical models used to optimize patrolling strategies. Patrolling is a critical crime prevention and deterrence strategy, requiring the effective allocation of resources to address evolving security challenges. In addition, patrolling is one of the most effective and widely adopted crime prevention and deterrence strategies worldwide. It is integral to security agencies such as police and military forces across various domains, including land, air, and maritime areas. As such, effective patrolling requires the coordination of manpower, technological resources, and policies to address evolving security challenges. The authors review recent research on robotic patrolling, multirobot systems, and police patrolling and also explore advances in modeling, optimization, and practical applications. In addition, the author's analysis categorizes studies by core modeling themes, such as Game Theory, Mathematical Optimization, and Stochastic methods, and highlights the secondary modeling themes that frequently complement the primary approaches. Each study is categorized by fields including, but not limited to domain, patrolling focus, area representation, and solution methodology to facilitate cross-comparison. The book identifies gaps in current research, particularly the lack of a holistic examination of patrolling from robotic, autonomous, human, and hybrid perspectives, and proposes future directions for research in this evolving field.

商品描述(中文翻譯)

本書全面探討了各個領域的巡邏犯罪問題，包括機器人技術、安全和執法，重點在於用於優化巡邏策略的數學模型。巡邏是一種關鍵的犯罪預防和威懾策略，需要有效分配資源以應對不斷演變的安全挑戰。此外，巡邏是全球最有效且廣泛採用的犯罪預防和威懾策略之一。它對於各個領域的安全機構，如警察和軍隊，都是不可或缺的，包括陸地、空中和海洋區域。因此，有效的巡邏需要人力、技術資源和政策的協調，以應對不斷演變的安全挑戰。作者回顧了近期在機器人巡邏、多機器人系統和警察巡邏方面的研究，並探討了建模、優化和實際應用的進展。此外，作者的分析根據核心建模主題對研究進行分類，如博弈論（Game Theory）、數學優化（Mathematical Optimization）和隨機方法（Stochastic methods），並突顯了經常補充主要方法的次要建模主題。每項研究根據領域進行分類，包括但不限於領域、巡邏重點、區域表示和解決方法，以便進行交叉比較。本書指出了當前研究中的空白，特別是缺乏從機器人、自主、人類和混合視角對巡邏進行整體檢視，並提出了未來在這一不斷發展的領域中的研究方向。

作者簡介

Yusuf Ihsan Tokel is a Ph.D. candidate in the Department of Industrial and Systems Engineering at the University at Buffalo. His research interests focus on data-driven decision-making, game theory, and combinatorial optimization. He is interested in a niche area of game theory known as signaling theory, having already published on the topic. Additionally, he is conducting a data-driven study to analyze the smuggling activities internationally and understand immigration trends to the U.S. from countries outside of South and Central America, aiming to improve the accuracy of models in this under-studied domain. As part of his dissertation, he is developing mathematical optimization models to optimize resource allocation in dynamic security environments, while also using game-theoretic approaches to analyze strategic interactions with adaptive adversaries across various security contexts.

Jun Zhuang, Ph.D., is the Associate Dean for Research in the School of Engineering and Applied Sciences and the Morton C. Frank Professor in the Department of Industrial and Systems Engineering at the University at Buffalo, which is part of the State University of New York. Dr. Zhuang obtained his Ph.D. in Industrial Engineering from the University of Wisconsin-Madison in 2008. His primary research objective is to integrate operations research, big data analytics, game theory, and decision analysis to enhance mitigation, preparedness, response, and recovery in the face of natural and man-made disasters. Additionally, he explores other domains such as healthcare, sports, transportation, supply chain management, sustainability, and architecture. Dr. Zhuang has acted as a principal investigator for more than 40 research grants funded by various organizations, including the U.S. National Science Foundation (NSF), the U.S. Department of Homeland Security (DHS), the U.S. Department of Energy (DOE), the U.S. Air Force Office of Scientific Research (AFOSR), and the National Fire Protection Association (NFPA).

作者簡介(中文翻譯)

Yusuf Ihsan Tokel 是紐約州立大學水牛城分校工業與系統工程系的博士候選人。他的研究興趣集中在數據驅動的決策制定、博弈論和組合優化。他對博弈論中的一個小眾領域——信號理論特別感興趣，並已在該主題上發表過相關論文。此外，他正在進行一項數據驅動的研究，以分析國際間的走私活動，並了解來自南美和中美洲以外國家的移民趨勢，旨在提高這一尚未充分研究領域模型的準確性。作為其論文的一部分，他正在開發數學優化模型，以優化動態安全環境中的資源配置，同時利用博弈論方法分析與各種安全情境中適應性對手的戰略互動。

莊俊博士是紐約州立大學水牛城分校工程與應用科學學院的研究副院長，以及工業與系統工程系的莫頓·C·法蘭克教授。莊博士於2008年在威斯康辛大學麥迪遜分校獲得工業工程博士學位。他的主要研究目標是整合運籌學、大數據分析、博弈論和決策分析，以增強在自然災害和人為災害面前的減災、準備、應對和恢復能力。此外，他還探索其他領域，如醫療保健、體育、交通、供應鏈管理、可持續性和建築。莊博士擔任過40多項由各種組織資助的研究計畫的首席研究員，包括美國國家科學基金會（NSF）、美國國土安全部（DHS）、美國能源部（DOE）、美國空軍科學研究辦公室（AFOSR）和全國消防協會（NFPA）。

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