# OpenMines: A Light and Comprehensive Mining Simulation Environment for Truck Dispatching

arXiv: https://arxiv.org/abs/2404.00622 · HTML: https://mlsanity.com/paper/2404.00622/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Mar 2024.

## Built on by (most cited first, 2 of 2)

- [Reinforcement Learning with Curriculum-inspired Adaptive Direct Policy Guidance for Truck Dispatching](https://mlsanity.com/paper/2502.20845/) (2025)
- [Mining--Gym: A Configurable RL Benchmarking Environment for Truck Dispatch Scheduling](https://mlsanity.com/paper/2503.19195/) (2025)

## Abstract (arXiv)

Mine fleet management algorithms can significantly reduce operational costs and enhance productivity in mining systems. Most current fleet management algorithms are evaluated based on self-implemented or proprietary simulation environments, posing challenges for replication and comparison. This paper models the simulation environment for mine fleet management from a complex systems perspective. Building upon previous work, we introduce probabilistic, user-defined events for random event simulation and implement various evaluation metrics and baselines, effectively reflecting the robustness of fleet management algorithms against unforeseen incidents. We present ``OpenMines'', an open-source framework encompassing the entire process of mine system modeling, algorithm development, and evaluation, facilitating future algorithm comparison and replication in the field. Code is available in https://github.com/370025263/openmines.