Comparative analysis of Bellman-Ford and Dijkstra’s algorithms for optimal evacuation route planning in multi-floor buildings

Abstract

This study introduces a groundbreaking application of the Bellman-Ford algorithm for optimizing evacuation routes in multi-floor academic buildings, extending its traditional use in single-source shortest-path problems to address complex multiple- source multiple-exit (MSME) problems. A comprehensive computational model was developed, reflecting real-world evacuation scenarios and incorporating key constraints and assumptions. The model was rigorously benchmarked against a Dijkstra’s algorithm-based model, revealing a 3.5% improvement in the number of evacuees evacuated after the initial 9 seconds. Detailed simulation results and extended data analysis further substantiate these findings. While the current model assumes perfect evacuee compliance and overlooks human behavior, future research could address these limitations to enhance the model’s realism. This study significantly advances the field of emergency evacuation planning, offering valuable insights for emergency response practitioners, facility managers, and policymakers.

Keywords:

• Bellman-Ford algorithm
• evacuation planning
• buildings
• multiple-source multiple-exit (MSME) problems
• Emergency management
• optimal route selection

REVIEWING EDITOR:

• D. T. Pham, University of Birmingham, UK

SUBJECTS:

• Systems & Controls
• Fire Protection & Safety
• Building Regulations

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Notes on contributors

Ritesh Bhat

Dr. Ritesh Ramakrishna Bhat is a distinguished Professor and Head of the Mechatronics Engineering Department at Rajalakshmi Engineering College. He possesses a robust academic and research background in areas such as Industrial Automation, Robotics and CNCs, Manufacturing Engineering, Industrial Engineering, Operations Research, and Production Management. Dr. Bhat’s academic credentials include a Ph.D. from Manipal Academy of Higher Education, an M.Tech. in Production Management, and a B.E. in Mechanical Engineering. With a publication record of over 35 articles in prestigious journals, his research significantly contributes to optimizing machining processes and advancing manufacturing practices. Recognized for his excellence with several awards, Dr. Bhat’s work impacts both academia and industry, focusing on curriculum development, industry partnerships, and student mentorship.

P. Krishnanda Rao

Dr. P. Krishnananda Rao is a Professor in the Department of Mechanical & Industrial Engineering, bringing extensive experience from 1994 to the present at Manipal Institute of Technology, MAHE, Manipal. Holding qualifications in BE, ME, and Ph.D., his academic journey and professional tenure reflect a deep engagement in Industrial Engineering. Dr. Rao specializes in Statistical Quality Control, Work Systems Engineering, and Total Quality Management, with a focused research interest in Cellular Manufacturing. His professional affiliations underscore his commitment to the field, being a Fellow of The Institution of Engineers (India) and a member of the Indian Society for Technical Education.

C. Raghavendra Kamath

Dr. C. Raghavendra Kamath is a professor in the Department of Mechanical and Industrial Engineering, MIT Manipal, India. He has more than 20 years of teaching and research experience. He has published a patent on machine vision. He also co-authored a book titled “Data Analysis Theoretical concepts for non-IT engineers”. He also has received a grant for research proposal titled “Cryogenic machining of elastomers” in 2019. He has presented and published more than 50 papers in various national and international journals and conferences. His research areas include machine/deep learning, image processing, non-conventional machining, cryogenic machining, difficult to machine materials, composite materials, optimization techniques, Operations research, Simulation modeling and analysis, Modeling of machining processes.

Vipin Tandon

Dr. Vipin Tandon is an Assistant Professor and Allied Faculty at Manipal School of Architecture and Planning, Manipal Academy of Higher Education, specializing in Metallurgical and Materials Engineering. His Ph.D. centered on the corrosion properties of AISI 316L and its dissimilar welds with AISI 201 steel. Dr. Tandon’s research encompasses Corrosion Engineering, Welding of Metals and Alloys, Surface Modification, and Nanocomposite Coatings. Recently, he has cultivated a special interest in sustainable building design, integrating his expertise in materials engineering with environmental sustainability principles to contribute to the field of green architecture and construction.

Prashant Vizzapu

Mr. Prashant Vizzapu is a dynamic analytics professional currently serving as Manager - Analytics at Tredence Inc., with experience across diverse roles in analytics consultancy and strategy. His journey in the field spans over eight years, involving strategic consulting for Fortune 100 CPG clients in the Food and Beverages industry. Prashant holds a Master’s Degree in Business Analytics from the University of Connecticut School of Business and a Bachelor’s Degree in Mechanical Engineering from Manipal Institute of Technology. His work has significantly contributed to leveraging data and analytics for business growth, decision-making, and generating substantial sales impacts. Prashant’s expertise includes SQL, Python, and developing innovative solutions for enhanced data processing and reporting.