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A Nonhomogeneous Poisson Process Approach to the Optimal Selection from a Sequence of Relatively Best Objects

In: Probability and Statistical Models in Operations Research, Computer and Management Sciences

Author

Listed:
  • Mitsushi Tamaki

    (Aichi University)

  • Qi Wang

    (Nagasaki Institute of Applied Science)

  • Tetsuya Tamaki

    (Kagawa University)

Abstract

A fixed known number n of rankable objects appear one at a time with all n! permutations equally likely. An object is called candidate if it is relatively best. As each candidate appears, we must decide either to choose it, or reject it and continue observations until the next candidate appears. Denote by $$C_{k}$$ C k the kth to last candidate. For the one-choice problem, a reward $$\alpha _{k}$$ α k is earned if $$C_{k}$$ C k is chosen and the objective is to find a stopping rule that maximizes the expected reward of the chosen candidate. Some cases with particular reward sequences $$\left\{ \alpha _{k}\right\} $$ α k are examined in the limiting form. The two-choice problem is also considered, where the reward is $$\alpha _{i, j}$$ α i , j if $$C_{i}$$ C i and $$C_{j}$$ C j are both chosen for $$i

Suggested Citation

  • Mitsushi Tamaki & Qi Wang & Tetsuya Tamaki, 2024. "A Nonhomogeneous Poisson Process Approach to the Optimal Selection from a Sequence of Relatively Best Objects," Springer Series in Reliability Engineering, in: Syouji Nakamura & Katsushige Sawaki & Toshio Nakagawa (ed.), Probability and Statistical Models in Operations Research, Computer and Management Sciences, pages 135-165, Springer.
  • Handle: RePEc:spr:ssrchp:978-3-031-64597-6_8
    DOI: 10.1007/978-3-031-64597-6_8
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