Title
A robust optimization solution to bottleneck generalized assignment problem under uncertainty
Abstract
We consider two versions of bottleneck (or min–max) generalized assignment problem (BGAP) under capacity uncertainty: Task–BGAP and Agent–BGAP. A robust optimization approach is employed to study this issue. The decision maker’s degree of risk aversion and the penalty weighting parameter are incorporated into the objective function. A state-of-the-art linearization method is introduced to deal with the mathematical model and find the solution scheme. Two penalties of weighting parameters that realize the trade-off between solution robustness and model robustness are obtained. Illustrative examples are presented with managerial implications highlighted for decision-making considerations.
Year
DOI
Venue
2015
10.1007/s10479-014-1631-5
Annals of Operations Research
Keywords
Field
DocType
Robust optimization,Bottleneck,Assignment,Stochastic programming
Bottleneck,Mathematical optimization,Weighting,Robust optimization,Computer science,Generalized assignment problem,Robustness (computer science),Stochastic programming,Linearization,Linear bottleneck assignment problem
Journal
Volume
Issue
ISSN
233
1
0254-5330
Citations 
PageRank 
References 
4
0.40
5
Authors
4
Name
Order
Citations
PageRank
Yelin Fu1478.26
Jianshan Sun219217.65
Kin Keung Lai31766203.01
John W. K. Leung4122.26