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...
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| Published in | Minerals (Basel) Vol. 13; no. 7; p. 966 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Basel
MDPI AG
01.07.2023
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2075-163X 2075-163X |
| DOI | 10.3390/min13070966 |
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| 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. |
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| AbstractList | 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. |
| Audience | Academic |
| Author | Ares, Gonzalo Álvarez, Isidro Diego Castañón Fernández, César |
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| Cites_doi | 10.5382/econgeo.4934 10.1016/j.cor.2019.06.013 10.1016/j.cor.2018.05.012 10.1016/S0375-6742(00)00150-3 10.1145/362384.362685 10.1007/s11053-022-10035-w 10.3390/min12040495 10.1080/17480930601118947 10.1007/978-1-4020-5717-5 10.1016/j.resourpol.2016.04.008 10.1007/978-3-642-83980-1 |
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| Copyright | COPYRIGHT 2023 MDPI AG 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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