Return
Efficient simulation for an open-pit mine
DOI:10.1016/j.simpat.2021.102473.png)
Abstract
En 中文
This paper presents an approach towards computationally efficient discrete-event-simulation designed to take advantage of high-performance computing architecture. We demonstrate how computational efficiency combined with large computing capacity enables quantification and mapping of stochastic system performance across a computationally challenging multidimensional parameter space requiring several million individual DES instances. An open-pit mine bulk materials handling system case study is presented to demonstrate the approach. A dispatching heuristic controlling the operation of the trucking system can be optimised through the selection of values for four control parameters. The multidimensional space represented by these control parameters is exhaustively mapped and visualised to provide insight into the relationships between combinations of parameters and system performance. The extensive data generated is ultimately used within a hyper-heuristic to determine near-optimal values for the dispatching heuristic control parameters.
Keywords:
Discrete event simulation
Open-pit mine
Dispatching
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.6
Papers:
2.6K
Citations:
4.8K
Organization
Cited Papers
Interactions between Seagrass Complexity, Hydrodynamic Flow and Biomixing Alter Food Availability for Associated Filter-Feeding Organisms
PLoS ONE
IF0

