Risk-averse two-stage stochastic programming with an application to disaster management

By Nilay Noyan. Computers & Operations Research, 2012

400 citations recorded by the source corpus.

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Incorporating risk measures in closed-loop supply chain network design (2014, methodology): “In such location-allocation problems, an efficient approach would be two-stage stochastic programming (Noyan 2012).”
Stochastic optimization models for location and inventory prepositioning of disaster relief supplies (2020, background): “…2007; Döyen et al., 2012; Mete and Zabinsky, 2010; Rawls and Turnquist, 2010), minimizing trade-off of total cost with Conditional Value-at-Risk (Noyan, 2012), minimizing expected response time (Duran et al., 2011), minimizing expected casualties (Salmerón and Apte, 2010), maximizing coverage…”
Multi-stage distributionally robust optimization with risk aversion (2021, methodology): “[33] considered a risk-averse two-stage stochastic programming model, where the Conditional Value-at-Risk (CVaR) was specified as the risk measure.”
Stochastic network design for disaster preparedness (2015, methodology): “Developing such two-stage stochastic models for the PRNDPs with inventory pre-positioning and relief distribution has recently received particular attention (Balcık and Beamon, 2008; Mete and Zabinsky, 2010; Rawls and Turnquist, 2010; Salmerón and Apte, 2010; Döyen et al., 2012; Noyan, 2012).”