Stochastic optimization of medical supply location and distribution in disaster management
By Huseyin Onur Mete, Zelda B. Zabinsky. 2010
732 citations recorded by the source corpus.
Subfields: Industrial and Manufacturing Engineering, Organizational Behavior and Human Resource Management
View Paper: https://www.semanticscholar.org/paper/4316223fb7a3c2e1b16bf123de60742b63a68283
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Industrial and Manufacturing Engineering
- Mustafa Alp Ertem
- Xin Hong
- Nilay Noyan
- Miguel A. P. M. Lejeune
- S. M. Al-e-hashem
- Mohamad Saeed Jabalameli
- Ali Bozorgi-Amiri
- Linet Özdamar
In Organizational Behavior and Human Resource Management
- Xin Hong
- Miguel A. P. M. Lejeune
- Mustafa Alp Ertem
- Nilay Noyan
- Emily L. Tucker
- Karmel S. Shehadeh
- S. M. Al-e-hashem
- Mohamad Saeed Jabalameli
Citations in the corpus
- Stochastic network design for disaster preparedness (2015, background): “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).”
- Models, solutions and enabling technologies in humanitarian logistics (2015, methodology): “Furthermore, inventory and equipment pre-positioning enable fast relief distribution to survivors from pre-stocked commodities (Balçık & Beamon, 2008; Duran, Gutierrez, & Keskinocak 2011; Ichoua, 2010; Mete & Zabinsky, 2010; Ukkusuri & Yushimito, 2008).”
- Optimization models in emergency logistics: A literature review (2012, background): “Among facility locationmodels combined with prepositioning and relief distribution, only Mete and Zabinski [46] optimize warehouse operations costs and total transportation time together.”
- Stochastic optimization models for location and inventory prepositioning of disaster relief supplies (2020, background): “Optimization criteria of these studies include minimizing the expected total cost (Chang et al., 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”
- A multi-objective robust stochastic programming model for disaster relief logistics under uncertainty (2011, background): “…of emergency commodities and necessity items by probabilistic scenarios representing disasters and their outcomes (see, e.g., Cormican et al. 1998; Barbarosoglu and Arda 2004; Beraldi et al. 2004; Chang et al. 2007; Beraldi and Bruni 2009; Mete and Zabinsky 2010; Rawls and Turnsquist 2010).”
- Investing in disaster management capabilities versus pre-positioning inventory: A new approach to disaster preparedness (2014, background): “, 2012) Early warning systems (Oloruntoba, 2010; Van Wassenhove, 2006) Decision-making models and tools (Adivar and Mert, 2010; Balcik and Beamon, 2008; Banomyong and Sopadang, 2010; Day et al., 2009; Görmez et al., 2011; Mete and Zabinsky, 2010; Nolz et al., 2010; Özdamar, 2011; Rawls and Turnquist”