Innovative application of python-based AHP and TOPSIS for fire safety management : a comprehensive framework for resource optimization

Abstract

Management of fire safety is an important aspect in the guarantee of the safety and ecological balance of manufactured structures. It also provides a framework for the efficient use of fire safety measures, energy, and water resources to reduce the hazards and enhance the rescue management. This paper presents an insightful framework which employs Python programming to apply Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) models for resources optimization in fire safety management. The development of a Python-based application that allows for structuring and sorting of resources by certain criteria such as cost, performance and compliance with fire safety regulations is the other key component of the engineering. The thesis consists of detailed review of relevant existing engineering management, fire safety management applications of AHP and TOPSIS as well with an effort of filling up the identified research gap. A novel methodology is proposed that integrates AHP for criteria weighting and TOPSIS for alternative ranking and administration in fire safety management. In the end the extent to which the methodology can be used in practice, through the use of real life examples in the allocation of fire safety resources, energy resources, and water resources. Key deliverables include designing AHP and TOPSIS algorithms in Python, resource allocation, and how these tools can essentially be utilized in fire safety management. The information provided in this project helps in developing AHP and TOPSIS that improve DMPs in relation to fire safety management and is easily accessible and understandable by the stakeholders. It is likely that the results will help deal with the issues of resource allocation, compliance with safety regulations as well as improve sustainability in the industry. By developing software with Python, this study has applied theoretical models from operational research to decision making developed models – AHP and TOPSIS, thus enabling the implementation of fire safety management. The results demonstrate the possibility of using engineering tools for solving complicated resource allocation problems