HUANG1993
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GreedRL-VRP-pretrained-v1

Reinforcement Learning

Deep Reinforcement Learning

Combinatorial Optimization

Reinforcement Learning

Vehicle Routing Problem

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HUANG1993 commited on Apr 20, 2023

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@@ -24,7 +24,8 @@ The entire architecture is divided into three layers:
     The constraints and optimization objectives for the problems to be solved are defined in the Reinforcement Learning(RL) Environment(Env).
     Based on performance and ease of use considerations, the Env framework provides two implementations:one based on **pytorch** and one based on **CUDA C++**.
     To facilitate the definition of problems for developers, the framework abstracts multiple variables to represent the environment's state, which are automatically generated after being declared by the user. When defining constraints and optimization objectives, developers can directly refer to the declared variables.
-Currently, various VRP variants such as CVRP, VRPTW and PDPTW, as well as problems such as Batching, are supported.
 * **Pluggable NN components**

     The constraints and optimization objectives for the problems to be solved are defined in the Reinforcement Learning(RL) Environment(Env).
     Based on performance and ease of use considerations, the Env framework provides two implementations:one based on **pytorch** and one based on **CUDA C++**.
     To facilitate the definition of problems for developers, the framework abstracts multiple variables to represent the environment's state, which are automatically generated after being declared by the user. When defining constraints and optimization objectives, developers can directly refer to the declared variables.
+    Currently, various VRP variants such as CVRP, VRPTW and PDPTW, as well as problems such as Batching, are supported.
 * **Pluggable NN components**