3 Presentations

• 
  09:00 AM - 09:25 AM

  Stochastic models for sealed reverse bid auction in humanitarian relief. A case study of the Colombian Red Cross

  • Diana C. Guzmán-Cortés, presenter, Universidad de La Sabana
  • Jean-François Cordeau, HEC Montréal, GERAD, CIRRELT
  • Marie-Eve Rancourt, HEC Montréal
  • Camilo Ortiz-Astorquiza, Université de Montréal
  • William J. Guerrero, Universidad de La Sabana

  Humanitarian organizations need to guarantee relief aid procurement in case of disasters situations since the preparation phase. For achieving it, they can use procurement reverse auctions. This work is focused on the announcement construction and bid construction stages for a public call of the Colombian Red Cross, using stochastic programming. Keywords: Reverse auction models, Humanitarian Logistics, Stochastic programming
• 
  09:25 AM - 09:50 AM

  Predictive models for food aid pre-positioning in humanitarian supply chains – A case study in South Sudan

  • Eeshaan Asaikar, presenter, HEC Montréal
  • Marie-Eve Rancourt, HEC Montréal
  • Valérie Bélanger, CIRRELT, HEC Montréal

  This research is based on a two-step approach to address food insecurity: 1) predictive modeling to estimate food-aid demand, 2) and inventory optimization to preposition supplies at strategic locations. This methodology is implemented and tested for the case of the World Food Programme’s operations in South Sudan.

  Keywords: Humanitarian logistics, inventory optimization, predictive analytics
• 
  09:50 AM - 10:15 AM

  Budget management in international humanitarian organizations

  • Milad Keshvari Fard, presenter, HEC Montréal
  • Ivana Ljubic, University of Vienna
  • Felix Papier, ESSEC Business School

  International Humanitarian Organizations (IHOs) run various missions and activities in several countries. Managing such large scale operations needs a meticulous planning regarding the missions to be done, the required skills and equipments, the target population, the human resources, etc., among other factors. Such decisions however, are tightly interconnected to the budget plans. Since the budget comes from donations, it is limited and its value is unknown beforehand, while a large part of it may be earmarked for specific countries or programs. The specific utility function of IHOs --which considers the social welfare of the beneficiaries as well as the fill rate of the planned missions--, renders budget management a challenging problem for IHOs. In this paper we model the problem as a two-stage decision process, where in the first stage the budget target for each national delegation is identified, and in the second stage, the optimal allocation of the non-earmarked budget among different countries is calculated. We then develop an efficient L-shaped algorithm as well as a fast heuristic to solve the problem. We use data from the International Committee of the Red Cross to extract our models' parameters, and conclude a number of interesting findings analytically and numerically. Our analysis indicates the importance of non-earmarked donations for the overall performance of IHOs. We also find out that putting a high pressure on IHO to fulfill the targeted missions (by donors, media, etc.) will result in a lower social welfare for beneficiaries. Finally our findings indicate that if donors allow the IHO to allocate the excessive earmarked donations to other delegations, the performance of IHO would improve significantly, and that the advantage of such scheme is increasing in the size of IHO.
  Keywords: International humanitarian organization; Earmarked donations; Budgeting; Nonlinear stochastic programming; Benders decomposition.