Ultimate Pit-Limit Optimization Algorithm Enhancement Using Structured Query Language

Three-dimensional block models are the most widely used tool for the study and evaluation of ore deposits, the calculation and design of economical pits, mine production planning, and physical and numerical simulations of ore deposits. The way these algorithms and computational techniques are progra...

Full description

Saved in:
Bibliographic Details
Published in:Minerals (Basel) 2023-07, Vol.13 (7), p.966
Main Authors: Ares, Gonzalo, Castañón Fernández, César, Álvarez, Isidro Diego
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Data base management systems
Database management systems
deposit modelization
floating cone
Language
Lithology
Mathematical optimization
mineral deposit
Mineral deposits
mining
Numerical analysis
Optimization
Ore deposits
Production planning
Programming languages
Queries
Query languages
Relational data bases
Spain
SQL
Structured Query Language-SQL
Three dimensional models
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Three-dimensional block models are the most widely used tool for the study and evaluation of ore deposits, the calculation and design of economical pits, mine production planning, and physical and numerical simulations of ore deposits. The way these algorithms and computational techniques are programmed is usually through complex C++, C# or Python libraries. Database programming languages such as SQL (Structured Query Language) have traditionally been restricted to drillhole sample data operation. However, major advances in the management and processing of large databases have opened up the possibility of changing the way in which block model calculations are related to the database. Thanks to programming languages designed to manage databases, such as SQL, the traditional recursive traversal of database records is replaced by a system of database queries. In this way, with a simple SQL, numerous lines of code are eliminated from the different loops, thus achieving a greater calculation speed. In this paper, a floating cone optimization algorithm is adapted to SQL, describing how economical cones can be generated, related and calculated, all in a simple way and with few lines of code. Finally, to test this methodology, a case study is developed and shown.
ISSN:2075-163X
2075-163X
DOI:10.3390/min13070966