A robust optimization solution to bottleneck generalized assignment problem under uncertainty

Yelin Fu (), Jianshan Sun (), K. Lai () and John Leung ()

Annals of Operations Research, 2015, vol. 233, issue 1, 123-133

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. Copyright Springer Science+Business Media New York 2015

Keywords: Robust optimization; Bottleneck; Assignment; Stochastic programming (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s10479-014-1631-5

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