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Optimal search for a randomly moving object

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R.R. Weber,
*J. Appl. Prob.* 23:708-717, 1986.

Abstract

It is desired to minimize the expected cost of finding an object which moves
back and forth between two location according to an unobservable Markov process.
When the object in in location $i$ $(i=1,2)$ it resides there for a time which
is exponentially distributed with parameter $\lambda$, and then moves to the
other location. The location of the object is not known and at each instant
until it is found exactly one of the two locations must be searched. Searching
location $i$ for a time $\delta$ costs $c_i\delta$ and conditional on the object
being in location $i$ there is a probability of $\alpha_i\delta+o(\delta)$ that
this search will find it. The probability that the object starts in location 1
is known to be $p_i(0)$. The location to be searched at time $t$ is to be
chosen on the basis of the value of $p_1(t)$, the probability that the object is
in location 1 given that it has not yet been discovered. We prove that there
exists a threshold $\Pi$ such that the optimal policy may be described as: {\em
search location 1 if and only if the probability that the object is in location
1 is greater than $\Pi$}. Expressions for the threshold $\Pi$ are given in
terms of the parameters of the model.

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