Development of Mathematical Model for Humanitarian Logistics Management: A Case Study of Floods Disaster

Abstract

This research is development of mathematical model for humanitarian logistics management for a case study of floods disaster in Thailand, using Integer Non-linear Programming (INLP) to determine the location of shelters and the amount of sufficient resources to help the victims. The developed model has been applied to case studies in flood-affected arear, Kantharawichai District, Maha Sarakham Province, which has a total area of 10 sub-districts, 183 villages and has a total of 82,764 victims. There are three villages, of which 570 victims are unable to live in the villages had to be moved to a shelter. The research specifies the scope or major limitations of the problem as follows: 1) there are two relief distribution centers, namely the Maha Sarakham Provincial Disaster Prevention and Mitigation Office and the Kantharawichai District Office, 2) there are 19 alternative shelter centers, which are in various government areas such as schools and temples, and 3) transport of victims and relief items will be used only by trucks. The proposed INLP model was processed with the LINGO 13.0 program. The results showed that two shelters should be opened. The Chumchon Makha School Center is opened for receiving the 164 victims from Kut Hua Chang Village, and the Ban Makok School Center is opened for receiving the 190 victims from Ban Khong Kut Wien, and 216 victims from Ban Huai Chan. For the 180 flood-affected villages, most of them were allocated relief items from Kantharawichai District Office which has a distance closer than from the Maha Sarakham Provincial Disaster Prevention and Mitigation Office. Moreover, both the transportation of the victims and the distribution of relief items should be transported by a 4-wheel operating truck. In addition, the solutions of proposed INLP model also showed that all victims are cover helped, with the minimize total operating cost of 20.859 million THB. Furthermore, the developed model can also be applied to larger scale flood disaster management as a result of the sensitivity analysis, and it can also be further developed for humanitarian logistics management in case of other types of disasters.