research
∙
01/05/2023
Training a Deep Q-Learning Agent Inside a Generic Constraint Programming Solver
Constraint programming is known for being an efficient approach for solv...
share
research
∙
12/16/2021
A prediction-based approach for online dynamic radiotherapy scheduling
Patient scheduling is a difficult task as it involves dealing with stoch...
research
∙
05/31/2021
Supervised learning and tree search for real-time storage allocation in Robotic Mobile Fulfillment Systems
A Robotic Mobile Fulfillment System is a robotised parts-to-picker syste...
research
∙
02/18/2021
SeaPearl: A Constraint Programming Solver guided by Reinforcement Learning
The design of efficient and generic algorithms for solving combinatorial...
research
∙
02/03/2021
Predicting the probability distribution of bus travel time to move towards reliable planning of public transport services
An important aspect of the quality of a public transport service is its ...
research
∙
01/21/2021
E-commerce warehousing: learning a storage policy
E-commerce with major online retailers is changing the way people consum...
research
∙
06/12/2020
Learning TSP Requires Rethinking Generalization
End-to-end training of neural network solvers for combinatorial problems...
research
∙
06/02/2020
Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization
Combinatorial optimization has found applications in numerous fields, fr...
research
∙
10/18/2019
A new constraint programming model and a linear programming-based adaptive large neighborhood search for the vehicle routing problem with synchronization constraints
We consider a vehicle routing problem which seeks to minimize cost subje...
research
∙
09/28/2019
How to Evaluate Machine Learning Approaches for Combinatorial Optimization: Application to the Travelling Salesman Problem
Combinatorial optimization is the field devoted to the study and practic...
research
∙
09/10/2018
