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SeaPearl: A Constraint Programming Solver guided by Reinforcement Learning
The design of efficient and generic algorithms for solving combinatorial...
02/18/2021 ∙ by Félix Chalumeau, et al. ∙
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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 ...
02/03/2021 ∙ by Léa Ricard, et al. ∙
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E-commerce warehousing: learning a storage policy
E-commerce with major online retailers is changing the way people consum...
01/21/2021 ∙ by Adrien Rimélé, et al. ∙
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Learning TSP Requires Rethinking Generalization
End-to-end training of neural network solvers for combinatorial problems...
06/12/2020 ∙ by Chaitanya K. Joshi, et al. ∙
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Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization
Combinatorial optimization has found applications in numerous fields, fr...
06/02/2020 ∙ by Quentin Cappart, et al. ∙
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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...
10/18/2019 ∙ by Minh Hoàng Hà, et al. ∙
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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...
09/28/2019 ∙ by Antoine François, et al. ∙
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Improving Optimization Bounds using Machine Learning: Decision Diagrams meet Deep Reinforcement Learning
Finding tight bounds on the optimal solution is a critical element of pr...
09/10/2018 ∙ by Quentin Cappart, et al. ∙
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