A Combined Diffusion Model and Reinforcement Learning Approach for Solving the Vehicle Routing Problem With Multiple Soft Time Windows

A Combined Diffusion Model and Reinforcement Learning Approach for Solving the Vehicle Routing Problem With Multiple Soft Time Windows

The Vehicle Routing Problem with Multiple Soft Time Windows (VRPMSTW) is a challenging combinatorial optimization problem where a fleet of vehicles must deliver goods to a set of customers, adhering to time windows while minimizing costs. In this paper, we propose a novel solution approach that comb...

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Bibliographic Details
Main Authors: Yu Qiao, Jianjun Miao, Xiaoying Huang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Vehicle routing problem (VRP)
multiple soft time windows (VRPMSTW)
diffusion model
reinforcement learning (RL)
combinatorial optimization
path generation
Online Access:https://ieeexplore.ieee.org/document/11053837/
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