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Minimizing the average searching time for an object within a graph

Author

Listed:
  • Ron Teller

    (Ben Gurion University of the Negev)

  • Moshe Zofi

    (Ben Gurion University of the Negev
    Sapir College)

  • Moshe Kaspi

    (Ben Gurion University of the Negev)

Abstract

This paper presents a new graph search problem for which a searcher wishes to find an object that may be found at a set of locations. The searcher doesn’t know the object’s exact location, but does know the a-prior probability of finding the object at each location. He wishes to build a searching path for reaching the object that starts from a given location and ends when reaching the object (or after searching the entire set with a false result). The objective is to find a searching path which will minimize the average searching time. We consider two scenarios for this problem: one when there is an unknown number of objects on the set and another when there is exactly one object on the set (the sum of probabilities is equal to 1). We show that this problem is NP-Hard, and supply a branch and bound algorithm for finding an optimal solution for large scale problems. We also study greedy approaches and other heuristics and compare the performance of these algorithms in various situations.

Suggested Citation

  • Ron Teller & Moshe Zofi & Moshe Kaspi, 2019. "Minimizing the average searching time for an object within a graph," Computational Optimization and Applications, Springer, vol. 74(2), pages 517-545, November.
  • Handle: RePEc:spr:coopap:v:74:y:2019:i:2:d:10.1007_s10589-019-00121-w
    DOI: 10.1007/s10589-019-00121-w
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    References listed on IDEAS

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    1. Lau, Haye & Huang, Shoudong & Dissanayake, Gamini, 2008. "Discounted MEAN bound for the optimal searcher path problem with non-uniform travel times," European Journal of Operational Research, Elsevier, vol. 190(2), pages 383-397, October.
    2. Hiroyuki Sato & Johannes O. Royset, 2010. "Path optimization for the resource‐constrained searcher," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(5), pages 422-440, August.
    3. Scott Shorey Brown, 1980. "Optimal Search for a Moving Target in Discrete Time and Space," Operations Research, INFORMS, vol. 28(6), pages 1275-1289, December.
    4. Arun Jotshi & Rajan Batta, 2009. "Investigating the benefits of re-optimisation while searching for two immobile entities on a network," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 1(1/2), pages 37-75.
    5. Jotshi, Arun & Batta, Rajan, 2008. "Search for an immobile entity on a network," European Journal of Operational Research, Elsevier, vol. 191(2), pages 347-359, December.
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