مشخصات پژوهش

عنوان	Humanitarian Logistics: Optimization Techniques for Preparedness and Post-Earthquake Response
نوع پژوهش	پایان نامه
کلیدواژه‌ها	Post-earthquake response, relief distribution system, Coverage path problem, Covering tour problem, UAV
چکیده	The most crowded cities in the world are located in high risk seismic areas. For humanitarian logistics system structure in highly populated cities we must search for fast and reliable monitoring and transportation methods with a futuristic mind. It is desirable to have a pre-planned immediate and automated post-disaster mapping, and transporting system. Due to roads blockage and time limits in the disaster response phase, Unmanned Aerial Vehicles (UAVs) can be utilized for relief distribution and rapid damage assessment. Also for medium to long-term ground response phase more complex but realistic models are needed. In this study we present relief distribution and damage assessment systems alongside mathematical linear programming formulations and heuristics. In an applied sense the research improves the emergency preparedness and post-earthquake response activities. A relief distribution system by medium-scale UAV helicopters is investigated and the outcomes reveal that the system has efficient capability for urban areas with high population density. Moreover, a rapid damage assessment system is presented in which multiple UAVs are deployed to collect the images from the earthquake site and create a response map for extracting useful information. Furthermore the covering tour location routing problem with replenishment at intermediate depots (CLRPR) is developed. The investigation represents a new bi-objective integer linear programming model that minimizes the total weighted waiting time and the total amount of lost demands. Among the different applications of the problem, this study concentrates on the post-earthquake relief distribution system. The mathematical models are coded in GAMS and solved by Cplex solver. Furthermore, some meta-heuristic algorithms are presented for CLRPR in order to find the near optimal solutions of large scale problems.
پژوهشگران	آرمان نجاتی (دانشجو)، گوکهان ایزبیراک (استاد راهنما)، جمال ارکات (استاد راهنما)