Dr. Edward Lam

Researcher in Combinatorial Optimization
Monash University

[email protected]
[email protected]

Edward is a Research Fellow in the Department of Data Science and Artificial Intelligence in the Faculty of Information Technology at Monash University, and contributes to the Analytics and Decision Sciences program at CSIRO Data61. His research in combinatorial optimization spans the disciplines of operations research in mathematics and artificial intelligence in computer science. He specializes in branch-and-cut-and-price for decompositions and hybridizations of integer programming and constraint programming.

Prior to joining Monash University, Edward completed his PhD studies at the University of Melbourne under the supervision of Pascal Van Hentenryck at the Georgia Institute of Technology. His thesis proposed novel techniques to hybridize integer programming, constraint programming and Boolean satisfiability; winning him the 2019 Doctoral Research Award from the Association for Constraint Programming.

Research Interests


Publications


Journal Articles

  1. Lam, E., Gange, G., Stuckey, P. J., Van Hentenryck, P., & Dekker, J. J. (2020). Nutmeg: A MIP and CP Hybrid Solver Using Branch-and-Check. SN Operations Research Forum, 1(3), 22. Download. Publisher. Source code.
  2. Lam, E., Van Hentenryck, P., & Kilby, P. (2020). Joint Vehicle and Crew Routing and Scheduling. Transportation Science, 54(2), 488–511. Download. Publisher.
  3. Lam, E., & Mak-Hau, V. (2020). Branch-and-cut-and-price for the cardinality-constrained multi-cycle problem in kidney exchange. Computers & Operations Research, 115, 104852. Download. Publisher.
  4. Lam, E., & Van Hentenryck, P. (2016). A branch-and-price-and-check model for the vehicle routing problem with location congestion. Constraints, 21(3), 394–412. Download. Publisher.

Conference Proceedings

  1. Lam, E., & Le Bodic, P. (2020). New Valid Inequalities in Branch-and-Cut-and-Price for Multi-Agent Path Finding. In Proceedings of the Thirtieth International Conference on Automated Planning and Scheduling (ICAPS 2020) (Vol. 30, pp. 184–192). Download. Publisher. Source code.
  2. Lam, E., de Nijs, F., Stuckey, P., Azuatalam, D., & Liebman, A. (2020). Large Neighborhood Search for Temperature Control with Demand Response. In H. Simonis (Ed.), Principles and Practice of Constraint Programming (CP 2020). Lecture Notes in Computer Science (Vol. 12333, pp. 603–619). Springer, Cham. Download. Publisher.
  3. Lam, E., Stuckey, P., Koenig, S., & Kumar, T. K. S. (2020). Exact Approaches to the Multi-Agent Collective Construction Problem. In H. Simonis (Ed.), Principles and Practice of Constraint Programming (CP 2020). Lecture Notes in Computer Science (Vol. 12333, pp. 743–758). Springer, Cham. Download. Publisher.
  4. Lam, E., Le Bodic, P., Harabor, D., & Stuckey, P. J. (2019). Branch-and-Cut-and-Price for Multi-Agent Pathfinding. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI 2019) (pp. 1289–1296). International Joint Conferences on Artificial Intelligence Organization. Download. Publisher. Source code.
  5. Lam, E., & Van Hentenryck, P. (2017). Branch-and-Check with Explanations for the Vehicle Routing Problem with Time Windows. In J. C. Beck (Ed.), Principles and Practice of Constraint Programming (CP 2017). Lecture Notes in Computer Science (Vol. 10416, pp. 579–595). Springer, Cham. Download. Publisher.
  6. Lam, E., Van Hentenryck, P., & Kilby, P. (2015). Joint Vehicle and Crew Routing and Scheduling. In G. Pesant (Ed.), Principles and Practice of Constraint Programming (CP 2015). Lecture Notes in Computer Science (Vol. 9255, pp. 654–670). Springer, Cham. Download. Publisher.

PhD Thesis

  1. Lam, E. (2017). Hybrid optimization of vehicle routing problems. University of Melbourne. Download. University archive.

Links