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.
https://doi.org/10.1155/2018/2453185Cite as:
@article{Bouzarth_2018,
doi = {10.1155/2018/2453185},
url = {https://doi.org/10.1155%2F2018%2F2453185},
year = 2018,
month = {oct},
publisher = {Hindawi Limited},
volume = {2018},
pages = {1--14},
author = {Elizabeth L. Bouzarth and Richard J. Forrester and Kevin R. Hutson and Rahul Isaac and James Midkiff and Danny Rivers and Leonard J. Testa},
title = {A Comparison of Algorithms for Finding an Efficient Theme Park Tour},
journal = {Journal of Applied Mathematics}
}