Hoong Chuin Lau's Research




Working at the interface of Artificial Intelligence and Operations Research, I am interested in combining data analytics and optimization for decision-making in business. More specifically, I make use of optimization models, agent-based models, and metaheuristics to solve use-inspired data-driven resource planning, scheduling and coordination problems in logistics, transportation, and supply chain management. Recently, my focus is on planning and scheduling problems in an urban shared economy. The common thread running through my research is a focus on going beyond papers to build usable novel tools and prototypes, a number of which have been testbedded and deployed in industry.


Research Leadership Roles:

·        Director, Fujitsu-SMU Urban Computing and Engineering Corp Lab (2014-now)

·        Coordinator, Urban Decision and Optimization Lab (2010-now)

·        Principal Investigator, Leisure & Tourism Experience Management Analytics group at the Living Analytics Research Center (2011-2015)


Research overview in slides and publicity articles:

·        Urban Computing and Engineering Corp Lab slides (press article in Business Times, video about lab projects)

·        Urban management and analytics slides (Asian Scientist article)

·        Leisure/Tourism experience management analytics slides (press article in Chinese 联合早报)

·        Defense logistics management poster (press release)


My research statement and a list of keynote/invited talks.


Editorial of Special Issues


·        Hoong Chuin Lau, Günther R. Raidl and Pascal Van Hentenryck. New developments in metaheuristics and their applications. Journal of Heuristics, 22:4, 2016. doi:10.1007/s10732-016-9313-x


·        Haolan Zhang and Hoong Chuin Lau. Agent-based problem solving methods in big data environment. Web Intelligence and Agent Systems Journal, IOS Press, 12:4, 2014.


·        Martin Bichler, Robert Kauffman, Hoong Chuin Lau, Christopher Yang and Yinping Yang. Proceedings of the 14th International Conference on Electronic Commerce, ACM Press, New York, 2012


A sample of systems and patent developed recently:




Theme Park Experience Management System and mobile app

Real-time interactive crowd movement flow tracking and coordination, and personalized itinerary planning in a theme park 


Personalized Conference Scheduling Agent (web and mobile app)

Targetted at visitors in large conferences and conventions, the app provides a list of recommended papers/talks based on keywords entered, and generates a personalized itinerary tailored to user schedule and preferences. The web system for AAMAS 2016 is available in: http://smu.sg/press

Crowd Management System

Singapore Patent Number 10201509975U granted on 24 August 2017.  The main claim is as follows:

A method for managing a crowd attending multiple capacity constrained resources comprising the steps of:

-       operatively connecting an operator via an internet connection to multiple users of the crowd to form a network;

-       determining a status of each capacity-constrained resource;

-       receiving a preferred order of attendance from each of multiple users;

-       for each user, computing a schedule based on the preferred order of attendance of the user and the status of each capacity constrained resource, wherein computing a schedule includes coordinating the schedules of multiple users;

-       for each user, presenting the personalized schedule to the user, wherein the schedule comprises the status of multiple capacity constrained resources; and

-       for each user, providing a personalized incentive to the user for following the schedule; and receiving real time updates on the status of each capacity-constrained resource and for at least one of multiple users, performing a re-computation of the schedule of the at least one of multiple users in response to the real time updates, wherein re-computation of the schedule is automatically performed without prompting from the user, and pushing out a real time update to the schedule based on the re-computed schedule using a push notification and an incentive to the user to follow the modified schedule.

Collaborative Urban Logistics platform (CLUE)

A web-based auction e-marketplace that enables carriers to collaborate on last-mile delivery through load consolidation via an Urban Consolidation Center  http://research.larc.smu.edu.sg/CLUE/

Adviser (Algorithm Portfolio Deviser)

Web-based tool that enables algorithm designers to finetune and select appropriate algorithms to solve optimization problems

http://research.larc.smu.edu.sg/adviserplus/ (Automated Algorithm Portfolio Devisor)

http://research.larc.smu.edu.sg/autopartune/ (Automated Parameter Tuning)


Highlights of Publications in reverse chronological order (see full publications)

Lucas Agussurja, Shih-Fen Cheng and Hoong Chuin Lau. State Aggregation Approach for Stochastic Multi-Period Last-Mile Ride-Sharing Problem. To appear in Transportation Science. [PDF]

Duc Thien Nguyen, Akshat Kumar and Hoong Chuin Lau. Credit Assignment For Collective Multiagent RL With Global Rewards. In Proc. Neural Information Processing Systems (NIPS), Montreal, Canada, December 2018. [PDF]

A. Gunawan, H. C. Lau and P. Vansteenwegen. Well-Tuned Algorithms for the Team Orienteering Problem with Time Windows. Journal of Operational Research Society, 68(8), 861-876, 2017. DOI: 10.1057/s41274-017-0244-1

T. V. Le, R. Oentaryo, S. Liu and H. C. Lau. Local Gaussian Processes for Efficient Fine-Grained Traffic Speed Prediction. IEEE Transactions on Big Data, 3(2), 2017. DOI: 10.1109/TBDATA.2016.2620488

A. Gunawan, H. C. Lau and P. Vansteenwegen. Orienteering Problem: A Survey of Recent Variants, Solution Approaches and Applications. European Journal of Operational Research, 225:2, 315-332, 2016. [PDF] See Orienteering Library.


D. Handoko, H. C. Lau and S. F. Cheng. Achieving Economic and Environmental Sustainability in Urban Consolidation Center with Bi-Criteria Auction.  IEEE Trans. Automation Science and Engineering, 13:4, 2016. [PDF]


T. Kandappu, A. Misra, S.F. Cheng, H. C. Lau, C. Chen, N. Jaiman, R. Tandriansyah, K. Dasgupta, and D. Chander. Campus-scale mobile crowd-tasking: Deployment and behavioral insights. In Proc. 19th ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW-16), San Francisco, CA, USA, February 2016. [PDF]


L. Agussurja, H. C. Lau and S. F. Cheng. Achieving Stable and Fair Profit Allocation with Minimum Subsidy in Collaborative Logistics. In Proc. 30th AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, Arizona, USA, February, 2016. [PDF]


C. Chen, S. F. Cheng, H. C. Lau and A. Misra. Towards City-scale Mobile Crowdsourcing: Task Recommendations under Trajectory Uncertainties. In Proc. International Joint Conference on Artificial Intelligence (IJCAI-15), Buenos Aires, Argentina, July 2015. [PDF]


N. Fu, H. C. Lau and P. Varakantham. Robust Execution Strategies for Project Scheduling under Unreliable Resources and Stochastic Durations. Journal of Scheduling, 2015.  [PDF]


R. Oentaryo, D. Handoko and H. C. Lau. Algorithm Selection via Ranking. In Proc. Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), Austin, Texas, USA, January, 2015. [PDF]


S. Saisubramanian, P. Varakantham and H. C. Lau. Risk based Optimization for Improving Emergency Medical Systems. In Proc. Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), Austin, Texas, USA, January, 2015. [PDF]


D. T. Nguyen, W. Yeoh, H. C. Lau, S. Zilberstein, and C. Zhang. Decentralized Multi-Agent Reinforcement Learning in Average-Reward Dynamic DCOPs. In Proc. Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI-14), Quebec City, Canada, July, 2014. [PDF]


H. C. Lau, Z. Yuan, and A. Gunawan. Patrol Scheduling in an Urban Rail Network. Annals of Operations Research. June 2014, 1-26. [PDF]


S. Hong, D. Zhang, H. C. Lau, and X. Zeng. A hybrid heuristic algorithm for the 2D variable-sized bin packing problem.  European Journal of Operational Research, 238:1, 2014, 95-103. [PDF]


A. Gunawan and H. C. Lau. Master Physician Scheduling Problem. Journal of the Operational Research Society, 64 (3), 410-425, 2013. [PDF]

H. C. Lau, L. Agussurja, S. F. Cheng, P. J. Tan. A Multi-Objective Memetic Algorithm for Vehicle Resource Allocation in Sustainable Transportation Planning. In Proc. International Joint Conference on Artificial Intelligence (IJCAI), Beijing, China, August 2013. [PDF]

P. Varakantham, H. C. Lau, and Z. Yuan. Scalable Randomized Patrolling for Securing Rapid Transit Networks. In Proc. Twenty Fifth Annual Conference on Innovative Applications of Artificial Intelligence (IAAI) organized as part of AAAI-2013, Bellevue, Washington, USA, July 2013. [PDF]

Lindawati, H. C. Lau and D. Lo. Clustering of Search Trajectory and its Application to Parameter Tuning. Journal of the Operational Research Society, 64, 1742–1752, 2013. [PDF]

N. Fu, H. C. Lau, P. Varakantham, and F. Xiao. Robust Local Search for Solving RCPSP/max with Durational Uncertainty. Journal of Artificial Intelligence Research, 43-86. 2012. [PDF]

L. Agussurja and H. C. Lau. Toward Large-Scale Agent Guidance in an Urban Taxi Service. In Proc. Conference on Uncertainty in Artificial Intelligence (UAI), Catalina Island, USA, Aug 2012. [PDF]

D. T. Nguyen, W. Yeoh, and H. C. Lau. Stochastic Dominance in Stochastic DCOPs for Risk Sensitive Applications. In Proc. 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Valencia, Spain, June 2012. [PDF]

H. C. Lau, Z. Zhao, S. Ge, T. H. Lee. Allocating resources in multi-agent flowshops with adaptive auctions. IEEE Trans. Automation Science and Engineering, 8(4), 732-743, 2011. [PDF]

H. C. Lau, J. Pan, and H. Song. Periodic Resource Reallocation in Two-Echelon Repairable Item Inventory Systems, IEEE Trans. Automation Science and Engineering, 7:3, 474–485, 2010. [PDF]

A. Liang, X. Wu, H. C. Lau,  Optimizing Service Systems based on Application-Level QoS. IEEE Trans. Service Computing, 2:2, 108-121, 2009. [PDF]

G. Feng and H. C. Lau. Efficient Algorithms for Machine Scheduling Problems with Earliness and Tardiness Penalties. Annals of Operations Research (Special Issue on Scheduling), 159, 83-95, 2008.  [PDF]

H. C. Lau, T. Ou and F. Xiao. Robust Local Search and Its Application to Generating Robust Schedules. In Proc. International Conf. on Automated Planning and Scheduling (ICAPS), Rhode Island, USA, September, 2007. [PDF]

S. Halim, R. Yap and H. C. Lau. An Integrated White+Black Box Approach for Designing and Tuning Stochastic Local Search. In Proc. 13th International Conf. on Principles & Practice of Constraint Programming (CP), Rhode Island, USA, September, 2007. [PDF]

H. C. Lau, H. Song, C. T. See and S. Y. Cheng. Evaluation of Time-Varying Availability in Multi-Echelon Spare Parts Systems with Passivation, European J. Operational Research. 170:1, 2006, 91-105.  [PDF]

H. C. Lau, T. Ou and M. Sim, Robust Temporal Constraint Networks. In Proc. 17th IEEE Conf. on Tools with Artificial Intelligence (ICTAI), 82-88, Hong Kong, November 2005. [PDF]


Y. Song and H. C. Lau, A Periodic-Review Inventory Model with Application to the Continuous-Review Obsolescence Problem, European J. Operational Research, 159:1, 2004, 110-120. [PDF]


H. C. Lau, K. M. Ng, and X. Wu. Transport Logistics Planning with Service-Level Constraints. In Proc. 19th National Conf. on Artificial Intelligence (AAAI), San Jose, USA, July 2004. 519-524. [PDF]


H. C. Lau, M. Sim and K. M. Teo, "Vehicle Routing Problem with Time Windows and a Limited Number of Vehicles", European J. Operational Research, 148:3, 2003, 559-569. [PDF]


H. C. Lau, H. Ono, and Q. Z. Liu. Integrating Local Search and Network Flow to Solve the Inventory Routing Problem. In Proc. 18th National Conf. on Artificial Intelligence (AAAI), 9-14, Edmonton, Canada, 2002.  [PDF]


H. C. Lau, A New Approach for Weighted Constraint Satisfaction. Constraints Journal, 7:2, 2002, 150-165. [PDF]


H. C. Lau, Z. Liang, Pickup and Delivery Problem with Time Windows, Algorithms and Test Case Generation. Int. J. Artificial Intelligence Tools, 11:3, 2002, 455-472. [PDF]

H. C. Lau, Y. F. Lim, and Q. Z. Liu, Diversification of Search Neighborhood via Constraint-Based Local Search and Its Applications to VRPTW. In Proc. 3rd International Workshop on Integration of AI and OR Techniques (CP-AI-OR), 2001, Kent, UK. [PDF]

H. C. Lau, A. Lim, and Q. Z. Liu. Solving a Supply Chain Optimization Problem Collaboratively. In Proc. 17th National Conf. on Artificial Intelligence (AAAI), 780-785, Texas, USA, 2000. [PDF]