Title: Dynamic Experience Management in Theme Parks via Coordination and Incentives
Introduction
Mobile computing has changed the way businesses engage with consumers. At the individual levels, smart mobile devices are equipped with GPS sensors that enable user locations to be tracked in real-time, which enable personalized location-based services to be provided. Consequently, there is an increasing trend toward use of mobile apps to plan and manage activities. At the corporate levels, such digital traces can be aggregated and analysed to accurate determine/predict demand patterns and congestion.
In this talk, I will present computational problems relating to the operation of theme parks. From the visitors’ perspective, the most important aspect is in maximizing their enjoyment in the park; while from the operator’s perspective, one aspect is in congestion management (relieving long wait-times for rides and shows). The key in satisfying both aspects lie in effective coordination of visitors through proper dynamic guidance and well-timed incentives.
This talk discusses two problems arising from visitor flow coordination. I will first present the problem relating to single-agent dynamic stochastic route guidance, which is a generalization of the Orienteering Problem (Prize-Collecting Traveling Salesman). I will present an efficient and effective search method, and a mobile application developed for a large theme park operator. I then describe the problem of smoothing out demands/congestion through the use of incentives which are communicated via mobile devices. Here, we consider a network where each agent (i.e. visitor) maximizes his utility of pleasure seeking. Since incentives themselves are resources that are limited, they need to be carefully allocated in order to achieve the desired outcome of reducing congestion. More precisely, given a certain incentive budget level, the goal is to distribute the incentives to different agents at different time points so that certain congestion thresholds are satisfied at equilibrium. We present a mathematical model on how a solution might be computed.
About the speaker:
LAU Hoong Chuin is Associate Professor of Information Systems and Deputy Director of the Living Analytics Research Centre at the Singapore Management University. He is a Singapore government scholar who received his Doctorate of Engineering degree in Computer Science from the Tokyo Institute of Technology (Japan), and BSc and MSc degrees in Computer Science from the University of Minnesota (Minneapolis). His research in the interface of Artificial Intelligence and Operations Research has been widely applied to decision support and optimization, and has contributed to advances of algorithms and applications to a variety of complex resource planning and scheduling problems in logistics, transportation, e-Commerce, health-care and tourism. He serves on the editorial board of the IEEE Transactions on Automation Science and Engineering. He is a chartered member and currently serves on the board of directors of the Chartered Institute of Logistics and Transportation (Singapore). He won the National Innovation and Quality Convention Star Award in 2006 and SMU Lee Kwan Yew Research Fellowship in 2008.