Ultimate Pit-Limit Optimization Algorithm Enhancement Using Structured Query Language.
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| Title: | Ultimate Pit-Limit Optimization Algorithm Enhancement Using Structured Query Language. |
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| Authors: | Ares, Gonzalo, Castañón Fernández, César, Álvarez, Isidro Diego |
| Source: | Minerals (2075-163X); Jul2023, Vol. 13 Issue 7, p966, 20p |
| Subject Terms: | OPTIMIZATION algorithms, DATABASES, PROGRAMMING languages, ORE deposits, DATABASE design, PYTHON programming language, SQL |
| Abstract: | 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. [ABSTRACT FROM AUTHOR] |
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| Database: | Complementary Index |
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