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Genetic Algorithm for Optimizing Routing Design and Fleet Allocation of Freeway Service Overlapping Patrol

Author

Listed:
  • Xiuqiao Sun

    (School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150001, China)

  • Jian Wang

    (School of Management, Harbin Institute of Technology, Harbin 150001, China)

  • Weitiao Wu

    (School of Civil and Transportation Engineering, South China University of Technology, Guangzhou 510641, China)

  • Wenjia Liu

    (School of Management, Harbin Institute of Technology, Harbin 150001, China)

Abstract

The freeway service patrol problem involves patrol routing design and fleet allocation on freeways that would help transportation agency decision-makers when developing a freeway service patrols program and/or altering existing route coverage and fleet allocation. Based on the actual patrol process, our model presents an overlapping patrol model and addresses patrol routing design and fleet allocation in a single integrated model. The objective is to minimize the overall average incident response time. Two strategies—overlapping patrol and non-overlapping patrol—are compared in our paper. Matrix encoding is applied in the genetic algorithm (GA), and to maintain population diversity and avoid premature convergence, a niche strategy is incorporated into the traditional genetic algorithm. Meanwhile, an elitist strategy is employed to speed up the convergence. Using numerical experiments conducted based on data from the Sioux Falls network, we clearly show that: overlapping patrol strategy is superior to non-overlapping patrol strategy; the GA outperforms the simulated annealing (SA) algorithm; and the computational efficiency can be improved when LINGO software is used to solve the problem of fleet allocation.

Suggested Citation

  • Xiuqiao Sun & Jian Wang & Weitiao Wu & Wenjia Liu, 2018. "Genetic Algorithm for Optimizing Routing Design and Fleet Allocation of Freeway Service Overlapping Patrol," Sustainability, MDPI, vol. 10(11), pages 1-15, November.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:11:p:4120-:d:181749
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    References listed on IDEAS

    as
    1. Sun, Xiuqiao & Wang, Jian, 2018. "Routing design and fleet allocation optimization of freeway service patrol: Improved results using genetic algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 205-216.
    2. Dewil, R. & Vansteenwegen, P. & Cattrysse, D. & Van Oudheusden, D., 2015. "A minimum cost network flow model for the maximum covering and patrol routing problem," European Journal of Operational Research, Elsevier, vol. 247(1), pages 27-36.
    3. Yafeng Yin, 2008. "A Scenario-based Model for Fleet Allocation of Freeway Service Patrols," Networks and Spatial Economics, Springer, vol. 8(4), pages 407-417, December.
    4. Yafeng Yin, 2006. "Optimal Fleet Allocation of Freeway Service Patrols," Networks and Spatial Economics, Springer, vol. 6(3), pages 221-234, September.
    5. Chatterjee, Sangit & Carrera, Cecilia & Lynch, Lucy A., 1996. "Genetic algorithms and traveling salesman problems," European Journal of Operational Research, Elsevier, vol. 93(3), pages 490-510, September.
    6. Keskin, Burcu B. & Li, Shirley (Rong) & Steil, Dana & Spiller, Sarah, 2012. "Analysis of an integrated maximum covering and patrol routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 215-232.
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