[Scheduling seminar] Petr Vilim (OptalCP) and Vilem Heinz (CTU in Prague) | February 4 | OptalCP: Constraint Programming with Parallel Search and Reinforcement Learning-Based Acceleration

Dear scheduling researcher,

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

-- 
Zdenek Hanzalek
Industrial Informatics Department,
Czech Institute of Informatics, Robotics and Cybernetics,
Czech Technical University in Prague,
Jugoslavskych partyzanu 1580/3, 160 00 Prague 6, Czech Republic
https://rtime.ciirc.cvut.cz/~hanzalek/

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