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Limiting Behavior of the Target-Dependent Stochastic Sequential Assignment Problem

  • Golshid Baharian (a1) and Sheldon H. Jacobson (a1)

Abstract

The stochastic sequential assignment problem assigns distinct workers to sequentially arriving tasks with stochastic parameters. In this paper the assignments are performed so as to minimize the threshold probability, which is the probability of the long-run reward per task failing to achieve a target value (threshold). As the number of tasks approaches infinity, the problem is studied for independent and identically distributed (i.i.d.) tasks with a known distribution function and also for tasks that are derived from r distinct unobservable distributions (governed by a Markov chain). Stationary optimal policies are presented, which simultaneously minimize the threshold probability and achieve the optimal long-run expected reward per task.

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Copyright

Corresponding author

Postal address: Research Center of CHU Sainte-Justine, 3175 Cote Sainte-Catherine, local A-714, Montreal, Québec H3T 1C5, Canada. Email address: gbahari2@illinois.edu
∗∗ Postal address: Department of Computer Science, 201 N. Goodwin Ave., Urbana, IL 61801, USA. Email address: shj@illinois.edu

References

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[5] Baharian, G. and Jacobson, S. H. (2013). Limiting behavior of the stochastic sequential assignment problem. Naval Res. Logistics 60, 321330.
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Limiting Behavior of the Target-Dependent Stochastic Sequential Assignment Problem

  • Golshid Baharian (a1) and Sheldon H. Jacobson (a1)

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