The thesis investigates how Agent-Based Modeling and Simulation (ABMS) and Queueing Theory (QT) techniques help manage mass gathering (MG) crowds. The techniques are applied to Hajj MG, which is one of the most complex annual MG, with a focus on its challenging Tawaf ritual. The objective is to develop a Tawaf Decision Support System (DSS) to better understand Tawaf crowd dynamics and discover decisions that lead to superior performance. TawafSIM is an ABMS model in the DSS, which simulates macro-level Tawaf crowd dynamics through micro-level pilgrim modeling to explore the impact of crowd characteristics, facility layout, and management preferences on emergent crowd behaviours with respect to throughput, satisfaction, health, and safety. Whereas, TawafQT is a QT model in the DSS to explore the impact of pilgrim arrival rate and Tawaf throughput on expected arrival, departure, and waiting times along with average queue length in the Tawaf waiting area. The thesis provides several contributions, including the following. First, it is the only Tawaf research to use a hybrid ABMS and QT approach. Second, TawafSIM is a comprehensive Tawaf simulator. It incorporates features for pilgrim characteristics, facility design, and management preferences. It calculates eight metrics for Tawaf performance, which includes one for throughput, three for satisfaction, one for health, and three for safety. It is the only Tawaf simulator to estimate satisfaction and spread of infectious disease. It conducts 42 simulation experiments in 12 categories. It generates observations for emergent, tipping point, expected, and counter intuitive behaviours. It recommends a default scenario as the best decision along with a small subset of alternative scenarios, which provide above average Tawaf performance. It generates a Tawaf Crowd Management Guide to better understand Tawaf crowd dynamics and how to pursue above average Tawaf performance under different conditions. Third, TawafQT is the only study of the Tawaf waiting area. It uses an accurate queueing model with finite source, single service, and PH type distribution, which is not only applicable to the Tawaf and other Hajj related queueing systems but also to any queueing system, which has finite population and single service characteristics.

The thesis investigates how Agent-Based Modeling and Simulation (ABMS) and Queueing Theory (QT) techniques help manage mass gathering (MG) crowds. The techniques are applied to Hajj MG, which is one of the most complex annual MG, with a focus on its challenging Tawaf ritual. The objective is to develop a Tawaf Decision Support System (DSS) to better understand Tawaf crowd dynamics and discover decisions that lead to superior performance. TawafSIM is an ABMS model in the DSS, which simulates macro-level Tawaf crowd dynamics through micro-level pilgrim modeling to explore the impact of crowd characteristics, facility layout, and management preferences on emergent crowd behaviours with respect to throughput, satisfaction, health, and safety. Whereas, TawafQT is a QT model in the DSS to explore the impact of pilgrim arrival rate and Tawaf throughput on expected arrival, departure, and waiting times along with average queue length in the Tawaf waiting area. The thesis provides several contributions, including the following. First, it is the only Tawaf research to use a hybrid ABMS and QT approach. Second, TawafSIM is a comprehensive Tawaf simulator. It incorporates features for pilgrim characteristics, facility design, and management preferences. It calculates eight metrics for Tawaf performance, which includes one for throughput, three for satisfaction, one for health, and three for safety. It is the only Tawaf simulator to estimate satisfaction and spread of infectious disease. It conducts 42 simulation experiments in 12 categories. It generates observations for emergent, tipping point, expected, and counter intuitive behaviours. It recommends a default scenario as the best decision along with a small subset of alternative scenarios, which provide above average Tawaf performance. It generates a Tawaf Crowd Management Guide to better understand Tawaf crowd dynamics and how to pursue above average Tawaf performance under different conditions. Third, TawafQT is the only study of the Tawaf waiting area. It uses an accurate queueing model with finite source, single service, and PH type distribution, which is not only applicable to the Tawaf and other Hajj related queueing systems but also to any queueing system, which has finite population and single service characteristics.