An OR-based decision support system for crowd management during the Hajj
The Hajj the great Islamic pilgrimage to Makkah in Saudi Arabia is known to be the largest annually occurring pedestrian problem in the world. Each year up to 4 million pilgrims approach the holy sites at the region of Makkah to perform their religious duty. This figure is likely to grow substantially over the coming years. The key ritual “stoning-of-the-devil" is known to be particularly crowded. Until 2006, several sad crowd disasters (stampedes) led to thousands of casualties due to overcrowding. In the aftermath of the crowd disaster in 2006, the Ministry of Municipal and Rural Affairs of the Kingdom of Saudi Arabia (MOMRA) launched projects of total $7 billion to prevent crowd disasters in the future. In particular, MOMRA started to develop an OR-based decision support system (ORDSS) for crowd management that employs a range of tools from operations research, analytics, and crowd dynamics. At its heart a scheduling tool and a real-time video tracking system are implemented. While the video tracking systems measures actual infrastructure utilization, the mixed integer programming tool Pilgrim Scheduler accounts for preferred stoning times, infrastructure capacities, and smooth capacity utilization. Further analytics and operations research tools of the ORDSS assign pilgrims to trips and stations of a metro system that transports pilgrims during the Hajj, support the layout planning of the tent city accommodating the pilgrims, analyze and simulate pilgrim flows, and re-schedule pilgrims in case of critical densities. The ORDSS provides solutions to MOMRA that enable uncongested and smooth pilgrim flows as well as extensive real-time reporting. Operations research helped stop the tragic loss of human lives due to stampedes. 2007-2014 no crowd disaster has happened. The algorithms and their successful implementation in the crowd management of the Hajj and the integrative use of operations research will help to better manage mass gatherings all over the world.