Yardım malzemesi dağıtım operasyonlarının simülasyon ile analizi

Abstract

 Development of a simulation model for analysis of post-disaster relief supplies distribution operations  Estimation of earthquake intensity using a comprehensive disaster database and an artificial neural network  Analysis of simultaneous usage of central and local resources via the developed simulation model In this study, we develop a simulation model to analyze the simultaneous usage of both local and global resources in relief supplies distribution operations. In order to generate the scenarios of the simulation model, we use the significant earthquakes archive of the United States Geological Survey. We estimate earthquake intensity using the magnitude, depth and distance to the epicenter of an earthquake via an artificial neural network. In relation to the estimated earthquake intensity, we determine the affected population rate and disaster level. In addition to these two parameters, the number of pre-positioned Temporary-Disaster-Response facilities is presented as another scenario parameter for the simulation model. Our simulation model includes two main components as global and local, where we model the arrivals of the resources of central humanitarian organizations and local relief supplies distribution operations, respectively. Using the simulation model, inventory levels of Temporary-Disaster-Response facilities are controlled simultaneously with the relief supplies distribution operations of central humanitarian organizations. Proposed simulation model is run with the scenarios generated and the results are analyzed in terms of some performance variables. Figure A. Run-time layout of the simulation model Purpose: The purpose of the study is to illustrate the utilization of simulation for analyzing relief supply distribution operations in disaster operations management. Theory and Methods: A simulation model is developed to analyze the simultaneous usage of both local and global resources in relief supplies distribution operations. An artificial neural network is designed to estimate earthquake intensity using the magnitude, depth and distance to the epicenter of an earthquake, which is then used to determine the affected population rate and disaster level. Results: Using the simulation model, inventory levels of Temporary-Disaster-Response facilities are controlled simultaneously with the relief supplies distribution operations of central humanitarian organizations. Proposed simulation model is run with the scenarios generated and the results are analyzed in terms of some performance variables. Conclusion: This study illustrates the utilization of simulation for analyzing relief supply distribution operations in disaster operations management. A simulation model is developed to analyze the simultaneous usage of both local and global resources in relief supplies distribution operations. Although it is illustrated for a particular case, it can be extended to consider other general real-life problems.