ai4co / rl4co

A PyTorch library for all things Reinforcement Learning (RL) for Combinatorial Optimization (CO)
https://rl4.co
MIT License
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[Feat] Adding Multi-depot Capacity Pickup and Delivery Problem (MDCPDP) Environment #151

Closed cbhua closed 7 months ago

cbhua commented 7 months ago

Description

The multi-depot capacity pickup and delivery problem (MDCPDP) environment has the following definition:

Motivation and Context

Aside from previous simple pickup and delivery (PDP) environment, this new environment supports the following new features:

  1. Multi depots: there are more than one depot and each depot will have a vehicle, which makes the problem more flexible and complex;
  2. Lateness reward: we support the reward calculated as the lateness, i.e. cumulate sum of the arrival time to delivery nodes;
  3. Multi distance calculation modes: we support L1 and L2 distance calculation methods for more flexible reward calculation;
  4. Multi reward calculation modes: we support the lateness, lateness-square, min-max and min-sum reward calculation methods as objectives;
  5. Multi start modes: you could choose which depot starts firstly or let them randomly start;

Types of changes

Checklist

fedebotu commented 7 months ago

LGTM