Maximal Covering Location Problem for Pre-positioning and Emergency Supplies under Disasters

• Main Authors: Yu-En Wu, 吳育恩
• Other Authors: Tsai-Yun Liao
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/29236394403054929788

碩士 === 國立嘉義大學 === 行銷與運籌研究所 === 101 === The numbers of natural disasters have increased over recent years in Taiwan. Natural disasters not only threaten people's life but also cause huge property damage. In a large-scale natural disasters, anxiety of peoples and inaccurate information often result with delay in the progress of relief. Advanced preparation and pre-positioning of emergency supplies will effectively improve the speed of disaster relief process and reduce the loss of lives and property damage. In pre-positioning of emergency supplies, the key decisions are the locations and capacities of emergency distribution centers, as well as allocations of inventories of multiple relief commodities to those distribution locations. Also, it is important that critical relief supplies in pre-positioning locations can be delivered within a relatively short timeframe to meet the needs of people affected by the disasters. This study investigates maximal covering location problem (MCLP) for pre-positioning and emergency supplies under disasters. A MCLP model is developed to integrate facility location and inventory decisions for considering multiple item types, budgetary constraints, and capacity restrictions under various disaster scenarios. In order to illustrate the proposed model, the model is experimented numerically for the pre-positioning of emergency supply problem of typhoon in Kaohsiung City, Taiwan. LINGO solver is used to solve the model and analyze the results. The experiment results show that the model can be applied to generate pre-positioning solutions of emergency supplies for disaster response considering various disaster scenarios. Results of this study shows that 6 emergency distribution centers with different capacities should be established in Kaohsiung to maximize the coverage of the needs of emergency relief. These results and managerial implications of the proposed model can be used by government agencies in planning for disaster response.