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Deep Reinforcement Learning for Traveling Purchaser Problems
The traveling purchaser problem (TPP) is an important combinatorial optimization problem with broad applications.
A Reinforcement-Learning-Based Multiple-Column Selection Strategy for Column Generation
Column generation (CG) is one of the most successful approaches for solving large-scale linear programming (LP) problems.
The Neural-Prediction based Acceleration Algorithm of Column Generation for Graph-Based Set Covering Problems
In this paper, we propose an improved column generation algorithm with neural prediction (CG-P) for solving graph-based set covering problems.
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