A Framework to Implement Agent Based Modeling for Resources Allocation to Reduce Disaster Risk Factor in the Urban Environment of Pakistan

Abstract

Disaster can be an unlikely event, a sudden accident or a random chain of contingency worldwide that may result in unexpected consequences. Many developed countries have been working over the past few decades to reduce the risk factor of disasters by using different approaches to disaster management. But these efforts are in early stage of development in the developing countries, as these countries hardly get desired results due to insufficient resources in terms of technology. There is however a growing shift in disaster management, many developing countries need a framework and approaches to reduce the risk factor for disasters. Regardless of how much resource a country has and how well it has been developed, but these efforts cannot achieve desired results in term of sudden incident. In Pakistan, very few efficient work on disaster management is done till now. Pakistan urban environment is most affected from natural and human made disasters as compared to rural environment in context of road accident and fire. Our focus centered on human-made disaster. In our work, a framework to implement Agent Based Modeling for Resource Allocation is purposed. In this framework we used two allocation algorithm; High Severity Level and First Come First Serve. These two algorithm are simulated in Netlogo by creating a hypothetical scenario in Geographical Information System space. Different experiments are designed on demands & resources dataset for allocation. The results of experiments are compared according to different parameters . In the results we analyze average wait time, overall number of demands, execution time and unallocated demands for performance measure.