Sequential stochastic assignment problem with time-dependent random success rates

Golshid Baharian, Arash Khatibi, Sheldon H. Jacobson

Research output: Contribution to journalArticle


The sequential stochastic assignment problem (SSAP) allocates distinct workers with deterministic values to sequentially arriving tasks with stochastic parameters to maximize the expected total reward. In this paper we study an extension of the SSAP, in which the worker values are considered to be random variables, taking on new values upon each task arrival. Several SSAP models with different assumptions on the distribution of the worker values and closed-form expressions for optimal assignment policies are presented.

Original languageEnglish (US)
Pages (from-to)1052-1063
Number of pages12
JournalJournal of Applied Probability
Issue number4
StatePublished - Dec 1 2016


  • Sequential stochastic assignment
  • optimal policy

ASJC Scopus subject areas

  • Statistics and Probability
  • Mathematics(all)
  • Statistics, Probability and Uncertainty

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