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Found 7 papers, 3 papers with code
A Deep Reinforcement Learning Approach for Solving the Traveling Salesman Problem with Drone
Reinforcement learning has recently shown promise in learning quality solutions in many combinatorial optimization problems.
A Reinforcement Learning Approach for Rebalancing Electric Vehicle Sharing Systems
This paper proposes a reinforcement learning approach for nightly offline rebalancing operations in free-floating electric vehicle sharing systems (FFEVSS).
A Neural Separation Algorithm for the Rounded Capacity Inequalities
We design a learning-based separation heuristic algorithm with graph coarsening that learns the solutions of the exact separation problem with a graph neural network (GNN), which is trained with small instances of 50 to 100 customers.
An Attention-LSTM Hybrid Model for the Coordinated Routing of Multiple Vehicles
State-less attention-based decoder fails to make such coordination between vehicles.
A Hybrid Genetic Algorithm with Type-Aware Chromosomes for Traveling Salesman Problems with Drone
This study represents a hybrid genetic algorithm for solving TSPD and FSTSP by combining local search methods and dynamic programming.
A Hybrid Genetic Algorithm for the min-max Multiple Traveling Salesman Problem
This paper proposes a hybrid genetic algorithm for solving the Multiple Traveling Salesman Problem (mTSP) to minimize the length of the longest tour.
Genetic Algorithms with Neural Cost Predictor for Solving Hierarchical Vehicle Routing Problems
For each higher-level decision candidate, we predict the objective function values of the underlying vehicle routing problems using a pre-trained graph neural network without actually solving the routing problems.
