A Mixed Integer Programming optimization model for scheduling blood donors in disaster & emergency response: a case study of Nairobi region
Date
2019
Authors
Githogori, Samuel Maina
Journal Title
Journal ISSN
Volume Title
Publisher
Strathmore University
Abstract
In recent years, Kenya has experienced tragedies ranging from natural disasters such as floods, terrorist activities such as the Westgate and Garissa University attacks, man-made tragedies such as road accidents and collapsed building, as well as tragedies resulting from reckless human behavior, such as fuel siphoning, and building next to power lines. When such kinds of disasters and tragedies occur, they have historically caused serious injuries that sometimes cause death.
Also, during such events, medical emergencies arise, blood is one of the most critical components required by medial responder, and health facilities in order to perform transfusions that are necessary to save the lives of individuals. In the past, nationwide blood appeals have been conducted by authorities such as the Kenya Red Cross Society, media houses, politicians, and ordinary citizens, and Kenyans of Goodwill respond in large number at blood donation centers to donate blood. The challenge arising is that the system of appealing for blood is informal, unstructured and fragmented. It is difficult to track the effectiveness of ad-hoc methods of appealing for blood, and hard for potential blood donors to determine their eligibility in case they need to assist. The study proposed a mixed integer programming (MIP) model to optimize decision variables, which would determine the most optimal donation schedule and location for a given donor, based on whether they are eligible to donate, or not. The model sought to reduce the cost of responds, which is a function of the probability that a request for blood appeal will be posted, and the number of trips, distance, and cost it takes donor to respond. The model incorporated constraints such as donor availability within a given time block, and donor willingness to respond in a given region. The model’s outcome suggested that increased donor flexibility leads to a decrease in cost per donation session, and an increase in available regions increases donor flexibility, hence lower cost per donation intervention session on the donor.
Description
Thesis submitted in partial fulfillment of the requirements for the Degree of Master of Science in Information Technology (MSIT) at Strathmore University
Keywords
Blood donor, Disaster, Emergency, Mixed Integer Programming, Optimization