Analysis of a hypothetical humanitarian supply chain with agent-based simulation: The expected Istanbul earthquake

Abstract

All humanity has tragic memories and experiences of disasters. Disasters are low-probability events. In most cases, it is impossible to predict exactly when and where they will occur and what will be the devastating effects. However, many improvements can be made to reduce losses. According to estimates, as many as 2.5 million people may need emergency shelter after the expected Istanbul earthquake. The focus of this study is a hypothetical humanitarian supply chain to provide food and water to people in need of emergency shelters. An agent-based simulation (ABS) is created for the analysis. Software for the ABS model was developed with the Python programming language. Among agent-oriented software engineering methodologies, situational method engineering was chosen as a programming approach in the software development process. Agents of the model are smart objects that can have behavioral traits such as "parent", "mentally disabled", and "opportunist". The results indicate that panic among people can hinder the success rate of aid efforts, and relief operation plans that overlook individual differences are more likely to be unsuccessful.