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A Comparison of Algorithms for Finding an Efficient Theme Park Tour

Author

Listed:
  • Elizabeth L. Bouzarth
  • Richard J. Forrester
  • Kevin R. Hutson
  • Rahul Isaac
  • James Midkiff
  • Danny Rivers
  • Leonard J. Testa

Abstract

The problem of efficiently touring a theme park so as to minimize the amount of time spent in queues is an instance of the Traveling Salesman Problem with Time-Dependent Service Times (TSP-TS). In this paper, we present a mixed-integer linear programming formulation of the TSP-TS and describe a branch-and-cut algorithm based on this model. In addition, we develop a lower bound for the TSP-TS and describe two metaheuristic approaches for obtaining good quality solutions: a genetic algorithm and a tabu search algorithm. Using test instances motivated by actual theme park data, we conduct a computational study to compare the effectiveness of our algorithms.

Suggested Citation

  • Elizabeth L. Bouzarth & Richard J. Forrester & Kevin R. Hutson & Rahul Isaac & James Midkiff & Danny Rivers & Leonard J. Testa, 2018. "A Comparison of Algorithms for Finding an Efficient Theme Park Tour," Journal of Applied Mathematics, Hindawi, vol. 2018, pages 1-14, October.
    • Handle: RePEc:hin:jnljam:2453185
    DOI: 10.1155/2018/2453185
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    Cited by:

    1. Feng, Rui & Zhang, Jin & Wu, Yuelong & Wu, Ruibo & Yao, Baozhen, 2023. "School accessibility evaluation under mixed-load school bus routing problem strategies," Transport Policy, Elsevier, vol. 131(C), pages 75-86.
    2. Zhang Yang & Jiacheng Li & Lei Li, 2020. "Time-Dependent Theme Park Routing Problem by Partheno-Genetic Algorithm," Mathematics, MDPI, vol. 8(12), pages 1-20, December.

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