A bi-objective casualty collection point (CCP) location problem considering an uncertain casualties over a multi-period planning horizon is formulated
|Speaker:||Mehdi Amiri-Aref, Assistant Professor at the Department of Information Systems and Operation Management of Kedge Business School|
|Date: ||Friday 29 July 2016|
|Time: ||13:00 - 14:00|
|Location: ||Building One Marchant Syndicate Room A|
In this study, a bi-objective casualty collection point (CCP) location problem considering an uncertain casualties over a multi-period planning horizon is formulated. A two-stage stochastic programming model integrating the capacitated CCP locations and multi-period flow of casualties with a demand trend for the flow of casualties has been integrated in the model. The objectives of the model presented in this paper are the CCP closeness to affected areas and hospitals and the CCP remoteness from the disaster points at the first stage and casualties’ transportation cost from/to CCPs and holding cost at CCPs at the second stage. Reformulation to equivalent deterministic bi-objective model to generate sampling average approximation methods to solve for small instance has been implemented. A linear approximation and fuzzy goal programming-based approach is in progress to solve of the nonlinear part of the objective function is still in progress.
MEHDI AMIRI-AREF has been an assistant professor at the Department of Information Systems and Operation Management of Kedge Business School since September 2014. He was a postdoctoral researcher and lecturer at the same school from March 2014 to July 2015. He holds a PhD in Industrial Engineering obtained in 2013 and an MSc degree in Industrial Engineering specializing in Material Handling Systems in 2008; His areas of research interests are design and management of supply chains, strategy of distribution logistics networks, and decision making and performance evaluation of logistics networks. He was the principal author of several scientific articles published in international journals.