https://schedulingseminar.com/
We are delighted to announce the talk given by Petr Vilim (OptalCP) and
Vilem Heinz (CTU in Prague). The title is " OptalCP: Constraint
Programming with Parallel Search and Reinforcement Learning-Based
Acceleration ". The seminar will take place on Zoom on Wednesday,
February 4 at 14:00 UTC.
Join Zoom Meeting
https://cesnet.zoom.us/j/92404900677?pwd=HV03FRygB2sDF5X7xI7IL68aIU9XX9.1
Meeting ID: 924 0490 0677
Passcode: 249708
You can follow the seminar online or offline on our Youtube channel as
well:
https://www.youtube.com/channel/UCUoCNnaAfw5NAntItILFn4A
The abstract follows.
Constraint Programming (CP) is a powerful paradigm for solving hard
combinatorial optimization problems, especially in scheduling. In this
talk, we introduce OptalCP, a modern CP solver designed for scheduling,
and explain why its design is both practical and effective for
real-world instances. We begin with an overview of what CP is and how
models are defined using variables, domains, and constraints. We then
break down the essential components of a solver—propagation and
search—and show how OptalCP combines efficient propagation algorithms
with parallel search strategies: LNS, failure-directed search, and user
heuristics, all exchanging solutions to find better results faster. The
main part focuses on OptalCP’s internal solving strategy: Large
Neighborhood Search (LNS) for fast improvements, Failure-Directed Search
(FDS) for strong reasoning and bounds, and efficient propagation
algorithms for aggressive pruning. We explain why combining these
approaches is crucial. To demonstrate, we will show the solver on a live
example. In the last part, we present research results showing how
reinforcement learning - specifically multi-armed bandits (MAB) - can
accelerate complete CP search by reducing the explored search tree. This
approach achieves state-of-the-art performance on classical JobShop and
RCPSP scheduling benchmarks.
The next talk in our series will be Christian Blum (IIIA-CSIC) |
February 18 | CMSA: A Hybrid Metaheuristic for Combinatorial Optimization.
For more details, please visit https://schedulingseminar.com/
With kind regards
Zdenek Hanzalek, Michael Pinedo and Guohua Wan