Investigating fairness issues in disaster response planning

• Main Author: Tan, Jian Hui
• Other Authors: Nie Xiaofeng
• Format: Final Year Project
• Language: English
• Published: 2016
• Subjects: DRNTU::Engineering
• Online Access: http://hdl.handle.net/10356/68651
• Institution: Nanyang Technological University

Due to the many challenges surrounding disaster response and its planning, aid personnel already have a paramount amount of issues on their plate. Often, supply chain professionals are brought in to help in disaster response planning. However, the key problem remains the inherent differences in for-profit and humanitarian supply chains. One very important issue, which is issue in fairness, is always severely underrated. The constant neglect of these issues will have tremendous impact not only in the planning processes, but ultimately it weighs heavily on the welfare of the beneficiaries, which aid personnel are seeking to help. By ignoring these issues on fairness that are inherent in the current systems, the help will not be evenly spread amongst those affected by the disaster. This study is thus on the fairness issues in disaster response planning, and also how we could tackle the issue. The understanding of disasters, disaster management and the challenges faced in humanitarian logistics was key to comprehending the issue at hand. Using that understanding as a basis, the issue chosen to tackle was that of how demand was being met at different locations of demand, evaluated not only in a particular time period but also across many time periods. This sought to analyze the two aspects of equity and constancy. Equity was to ensure that resources were distributed evenly across the different locations, ensuring a fair satisfaction of everybody’s demand. Constancy was the evaluation of whether across many time periods, this fairness could be maintained or adhered to, where as time passes along, other issues will affect our disaster response planning. With these considerations in mind, mathematical formulations were created to models, where these models were then put to the test in demand settings with various parameters in place. Detailed works done of the mathematical formulations, calculations and considerations are also presented. Further recommendations that could be made are also available in the conclusion.