Journal of Mathematics and Statistics

OR/MS Applications in Mt. Merapi Disaster Management

Amril Aman, Toni Bakhtiar, Farida Hanum and Prapto Tri Supriyo

DOI : 10.3844/jmssp.2012.264.273

Journal of Mathematics and Statistics

Volume 8, Issue 2

Pages 264-273

Abstract

Problem statement: Much of researches on the management of disaster deal with their social aspects such as sociological and psychological effects on communities. Recently there had been a growing credit of the demand for application of the operational research and management science matters in disaster management. This approach commonly utilizes decision theory, dynamical system and optimization technique to minimize the cost and recovery time. Approach: In this study we provide a comprehensive resource allocation model for disaster management, which consists of logistics distribution and humanitarian aid workforce’s assignment problems. The former was formulated in the form of integer linear programming whose objective was to minimize the logistic demand shortage. While the later was framed into goal programming basis to minimize penalty cost. Results: We implement our models in Mt. Merapi disaster operation activities. We first carry out the problem of logistic distribution between affected areas and distribution centers in the city basis. We then organize the assignment of humanitarian workforces in disaster response and recovery actions. Workers from several volunteer communities were assigned regarding their preferences on task and time. Conclusion: Approaches by Operations Research and Management Science (OR/MS) not only efficiently and optimally solve the problem of logistic distribution and humanitarian assignment in accelerating disaster responses and recovery processes, but also offer flexibilities in dealing with the problem. In application, the scale of the problem can easily be extended.

Copyright

© 2012 Amril Aman, Toni Bakhtiar, Farida Hanum and Prapto Tri Supriyo. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.