TY - JOUR
T1 - The sequential stochastic assignment problem with random success rates
AU - Khatibi, Arash
AU - Baharian, Golshid
AU - Kone, Estelle R.
AU - Jacobson, Sheldon H.
N1 - Funding Information:
This research has been supported in part by the Air Force Office of Scientific Research under grant no. FA9550-10-1-0387 and the National Science Foundation under grant no. CMMI-0900226. This material is based upon work supported in part by (while the fourth author served at) the National Science Foundation. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the United States Government, the Air Force Office of Scientific Research, or the National Science Foundation.
Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2014/11/2
Y1 - 2014/11/2
N2 - Given a finite number of workers with constant success rates, the Sequential Stochastic Assignment problem (SSAP) assigns the workers to sequentially arriving tasks with independent and identically distributed reward values, so as to maximize the total expected reward. This article studies the SSAP, with some (or all) workers having random success rates that are assumed to be independent but not necessarily identically distributed. Several assignment policies are proposed to address different levels of uncertainty in the success rates. Specifically, if the probability density functions of the random success rates are known, an optimal mixed policy is provided. If only the expected values of these rates are known, an optimal expectation policy is derived. © 2014
AB - Given a finite number of workers with constant success rates, the Sequential Stochastic Assignment problem (SSAP) assigns the workers to sequentially arriving tasks with independent and identically distributed reward values, so as to maximize the total expected reward. This article studies the SSAP, with some (or all) workers having random success rates that are assumed to be independent but not necessarily identically distributed. Several assignment policies are proposed to address different levels of uncertainty in the success rates. Specifically, if the probability density functions of the random success rates are known, an optimal mixed policy is provided. If only the expected values of these rates are known, an optimal expectation policy is derived. © 2014
KW - Sequential decision-making
KW - assignment policy
KW - stochastic processes
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U2 - 10.1080/0740817X.2014.882530
DO - 10.1080/0740817X.2014.882530
M3 - Article
AN - SCOPUS:84905238929
SN - 0740-817X
VL - 46
SP - 1169
EP - 1180
JO - IIE Transactions (Institute of Industrial Engineers)
JF - IIE Transactions (Institute of Industrial Engineers)
IS - 11
ER -