Treffer: Network optimization for the design of underground mines

Title:
Network optimization for the design of underground mines
Source:
Multicommodity flows and network designNetworks (New York, NY). 49(1):40-50
Publisher Information:
New York, NY: John Wiley & Sons, 2007.
Publication Year:
2007
Physical Description:
print, 24 ref
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
ARC Special Research Centre for Ultra-Broadband Information Networks (CUBIN), Department of Electrical and Electronic Engineering, The University of Melbourne, Victoria 3010, Australia
ISSN:
0028-3045
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Building. Public works. Transport. Civil engineering

Computer science; theoretical automation; systems
Accession Number:
edscal.18405625
Database:
PASCAL Archive

Weitere Informationen

Efficient methods to model and optimize the design of open-cut mines have been known for many years. The design of the infrastructure of underground mines has a similar potential for optimization and strategic planning. In this article we discuss the use of network optimization to tackle this problem. The idea is to design a connected system of declines, ramps, drives, and possibly shafts, to minimize capital development and haulage costs over the lifetime of a mine. This can be modeled as a variation on the Steiner problem, with suitable metric and constraints. These constraints include: an upper bound on the absolute gradient of arcs in the embedded network (typically 1/7), turning circle restrictions for navigability, and obstacle avoidance. Here we give an overview of the literature, focussing on our published work. We investigate the way in which this design problem can be modeled as a network optimization problem that accurately reflects the real costs involved while remaining mathematically tractable. Our approach is to first establish a fundamental model, which principally captures the development costs of the mine, and to study its geometric properties. We then outline more complicated generalized models, which add extra costs and constraints to the fundamental model but are still solvable.