A Multi-stage Stochastic Programming for Redesigning the Relief Logistics Network: A Real Case Study

Disasters inevitably cause sweeping problems affecting all surroundings. Therefore, it seems that right decision making for agile and efficient management in disaster management is not negligible. Due to designed network in the past, current entities, facilities and network may not be optimal and to a great extent usable. In this paper a comprehensive model and solving approach have been proposed to redesign the relief network in dealing with the preparedness and response phases. In this regard, previous investigations on the preparedness phase have often been limited to the location of eligible facilities without considering other important factors such as current and working assets, entities and configuration. Thus, the present study proposes a reconfiguring and repositioning model in order to simultaneously assess whether existing distribution centers should remain, be consolidated or phased out as well as whether new facilities should be established and subsequently supply and demand requirements consideration. Moreover, in the proposed model, multi-stage stochastic programming has been implemented on a real data gathered by ArcGIS Software and demand scenarios derived from relevant references. The results based on a real case study in Tehran indicate definite advantages in the re-positioning or reconfiguring model compared with current configurations.