TY - JOUR
T1 - A bi-criteria multiple-choice secretary problem
AU - Yu, Ge
AU - Jacobson, Sheldon Howard
AU - Kiyavash, Negar
N1 - Funding Information:
Negar Kiyavash is a joint associate professor in the H. Milton Stewart School of Industrial & Systems Engineering (ISyE) and the School of Electrical and Computer Engineering (ECE) at Georgia Institute of Technology (Gatech). Prior to joining Gatech, when was a Willett Faculty Scholar at the University of Illinois and a joint associate professor of industrial and enterprise engineering (IE) and electrical and computer engineering (ECE). She received her Ph.D. degree in ECE from the University of Illinois at Urbana-Champaign in 2006. Her research interests are in design and analysis of algorithms for network inference and security. She is a recipient of NSF CAREER and AFOSR YIP awards and the Illinois College of Engineering Dean’s Award for Excellence in Research.
Funding Information:
This research has been supported in part by the Air Force Office of Scientific Research under Grant No. FA9550-15-1-0100. 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, or the Air Force Office of Scientific Research.
Publisher Copyright:
© 2019, Copyright © 2019 “IISE”.
PY - 2019/6/3
Y1 - 2019/6/3
N2 - This article studies a Bi-criteria Multiple-choice Secretary Problem (BMSP) with full information. A sequence of candidates arrive one at a time, with a two-dimensional attribute vector revealed upon arrival. A decision maker needs to select a total number of η candidates to fill η job openings, based on the attribute vectors of candidates. The objective of the decision maker is to maximize the expected sum of attribute values of selected candidates for both dimensions of the attribute vector. An approach for generating Pareto-optimal policies for BMSP is proposed using the weighted sum method. Moreover, closed-form expressions for values of both objective functions under Pareto-optimal policies for BMSP are provided to help a decision maker in the policy planning stage. These analysis techniques can be applied directly to solve the more general class of multi-criteria multiple-choice Secretary Problems, provided the objective functions are in the form of accumulating a product-form reward for each selected candidate.
AB - This article studies a Bi-criteria Multiple-choice Secretary Problem (BMSP) with full information. A sequence of candidates arrive one at a time, with a two-dimensional attribute vector revealed upon arrival. A decision maker needs to select a total number of η candidates to fill η job openings, based on the attribute vectors of candidates. The objective of the decision maker is to maximize the expected sum of attribute values of selected candidates for both dimensions of the attribute vector. An approach for generating Pareto-optimal policies for BMSP is proposed using the weighted sum method. Moreover, closed-form expressions for values of both objective functions under Pareto-optimal policies for BMSP are provided to help a decision maker in the policy planning stage. These analysis techniques can be applied directly to solve the more general class of multi-criteria multiple-choice Secretary Problems, provided the objective functions are in the form of accumulating a product-form reward for each selected candidate.
KW - Secretary Problem
KW - multi-objective online optimization
KW - sequential stochastic assignment
UR - http://www.scopus.com/inward/record.url?scp=85060891457&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85060891457&partnerID=8YFLogxK
U2 - 10.1080/24725854.2018.1516054
DO - 10.1080/24725854.2018.1516054
M3 - Article
AN - SCOPUS:85060891457
SN - 2472-5854
VL - 51
SP - 577
EP - 588
JO - IIE Transactions (Institute of Industrial Engineers)
JF - IIE Transactions (Institute of Industrial Engineers)
IS - 6
ER -