The vehicle routing problem with time windows and occasional drivers (VRPODTW) is an
extension of the vehicle routing problem with time windows, where ordinary people may …

The efficacy of robust optimization spans a variety of settings with uncertainties bounded in
predetermined sets. In many applications, uncertainties are affected by decisions and …

Including uncertainty in data envelopment analysis (DEA) is vital to achieving stable and
reliable performance evaluations for the field of operational research as business …

Abstract Robust Portfolio Modeling (RPM) supports multi-attribute project portfolio selection
with uncertain project scores and decision maker preferences. By determining non …

The type of decision dependent uncertainties (DDUs) imposes a great challenge in decision
making, while existing methodologies are not sufficient to support many real practices. In this …

This paper contemplates the use of robust optimization as a framework for addressing
problems that involve endogenous uncertainty, ie, uncertainty that is affected by the decision …

In the conventional robust optimization (RO) context, the uncertainty is regarded as residing
in a predeter-mined and fixed uncertainty set. In many applications, however, uncertainties …

We study a class of adversarial minimum-cost flow problems where the arcs are subject to
multiple ripple effect disruptions that increase their usage cost. The locations of the …

In this work we study min max robust scheduling problems assuming that the processing
times can take any value in the budgeted uncertainty set introduced by Bertsimas and Sim …

We study the design of resilient single-commodity flow networks that can remain robust
against multiple concurrent edge failures. We model these failures as binary random …