Domain-Independent Dynamic Programming for Combinatorial Optimization

J. Christopher Beck (University of Toronto)

25 September 2024, 12:45-14:15 | Echo-ARENA | Live-stream: https://collegerama.tudelft.nl/Mediasite/Channel/eemcs-cs-distinguished-speaker-lectures-cs-dsl/watch/677db5f2fba84c948db6dcee8835513a1d

Abstrat

Dynamic Programming is a powerful problem solving approach developed primarily through problem-specific algorithms in Computer Science and Operations Research. Domain-Independent Dynamic Programming (DIDP) is a novel a model-and-solve framework where problems are specified as dynamic programs in a declarative modeling language and then solved by a general-purpose solver. In this talk, I will introduce DIDP, show examples of problem modeling, discuss our heuristic search-based solver, and present numerical results showing strong performance compared to mixed integer programming and constraint programming on a variety of combinatorial optimization problems in area such as routing and scheduling

J. Christopher Beck

J. Christopher Beck is a Professor in the Department of Mechanical & Industrial Engineering at the University of Toronto. For over 25 years, Chris has explored intelligent problem solving in Artificial Intelligence and Operations Research through the frameworks of constraint programming, mixed integer programming, and heuristic search, publishing over 170 papers in international conferences and journals. He has served as the President of both the Executive Committee of the International Conference on Automated Planning and Scheduling and of the Association for Constraint Programming and is currently the Associate Editor-in-Chief of the Journal of Artificial Intelligence Research.

Deel deze pagina: