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Bi-criteria dynamic location-routing problem for patrol coverage

Author

Listed:
  • Shirley (Rong) Li

    (The University of Alabama, Tuscaloosa, USA)

  • Burcu B Keskin

    (The University of Alabama, Tuscaloosa, USA)

Abstract

In this paper, we address the problem of dynamic patrol routing for state troopers for effective coverage of highways. Specifically, a number of state troopers start their routes at temporary stations (TS), patrol critical locations with high crash frequencies, and end their shifts at other (or the same) TS so the starting points for the next period are also optimized. We determine the number of state troopers, their assigned routes, and the locations of the TS where they start and end their routes. The TS are selected from a given set of potential locations. The problem, therefore, is a multi-period dynamic location-routing problem in the context of public service. Our objective is to maximize the critical location coverage benefit while minimizing the costs of TS selections, vehicle utilizations, and routing/travel. The multi-objective nature of the problem is handled using an ɛ-constraint approach. We formulate the problem as a mixed integer linear programming model and solve it using both off-the-shelf optimization software and a custom-built, efficient heuristic algorithm. The heuristic, utilizing the hierarchical structure of the problem, is built on the decomposition of location and routing problems. By allowing routing to start from multiple locations, our model improves the coverage by as much as 12% compared with the single-depot coverage model.

Suggested Citation

  • Shirley (Rong) Li & Burcu B Keskin, 2014. "Bi-criteria dynamic location-routing problem for patrol coverage," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(11), pages 1711-1725, November.
    • Handle: RePEc:pal:jorsoc:v:65:y:2014:i:11:p:1711-1725
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    Citations

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    Cited by:

    1. Cong Wang & Zhongxiu Peng & Xijun Xu, 2021. "A Bi-Level Programming Approach to the Location-Routing Problem with Cargo Splitting under Low-Carbon Policies," Mathematics, MDPI, vol. 9(18), pages 1-34, September.
    2. Saint-Guillain, Michael & Paquay, Célia & Limbourg, Sabine, 2021. "Time-dependent stochastic vehicle routing problem with random requests: Application to online police patrol management in Brussels," European Journal of Operational Research, Elsevier, vol. 292(3), pages 869-885.
    3. Timothy J. Surendonk & Paul A. Chircop, 2020. "On the computational complexity of the patrol boat scheduling problem with complete coverage," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(4), pages 289-299, June.
    4. Chen, Xinyuan & Wu, Shining & Liu, Yannick & Wu, Weiwei & Wang, Shuaian, 2022. "A patrol routing problem for maritime Crime-Fighting," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    5. Johanna Leigh & Sarah Dunnett & Lisa Jackson, 2019. "Predictive police patrolling to target hotspots and cover response demand," Annals of Operations Research, Springer, vol. 283(1), pages 395-410, December.
    6. Maximilian Schiffer & Michael Schneider & Grit Walther & Gilbert Laporte, 2019. "Vehicle Routing and Location Routing with Intermediate Stops: A Review," Transportation Science, INFORMS, vol. 53(2), pages 319-343, March.
    7. Jaller, Miguel & Pahwa, Anmol, 2023. "Coping with the Rise of E-commerce Generated Home Deliveries through Innovative Last-mile Technologies and Strategies," Institute of Transportation Studies, Working Paper Series qt5t76x0kh, Institute of Transportation Studies, UC Davis.

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