کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
382637 660775 2016 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
New graph-based algorithms to efficiently solve large scale open pit mining optimisation problems
ترجمه فارسی عنوان
الگوریتم های مبتنی بر گراف جدید برای حل موثر مسائل بهینه سازی معدن روباز در مقیاس بزرگ
کلمات کلیدی
الگوریتم های بهینه سازی معدن؛ برنامه ریزی و زمان؛ توالی مسدود شدن معدن ؛ حد گودال نهایی؛ حد گودال محدود
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• Two graph-based algorithms are developed for large-scale mining problems.
• The proposed algorithms outperform other existing solution approaches.
• This study leads to a more applicable mining optimisation software system.

In the mining optimisation literature, most researchers focused on two strategic-level and tactical-level open-pit mine optimisation problems, which are respectively termed ultimate pit limit (UPIT) or constrained pit limit (CPIT). However, many researchers indicate that the substantial numbers of variables and constraints in real-world instances (e.g., with 50–1000 thousand blocks) make the CPIT's mixed integer programming (MIP) model intractable for use. Thus, it becomes a considerable challenge to solve the large scale CPIT instances without relying on exact MIP optimiser as well as the complicated MIP relaxation/decomposition methods. To take this challenge, two new graph-based algorithms based on network flow graph and conjunctive graph theory are developed by taking advantage of problem properties. The performance of our proposed algorithms is validated by testing recent large scale benchmark UPIT and CPIT instances’ datasets of MineLib in 2013. In comparison to best known results from MineLib, it is shown that the proposed algorithms outperform other CPIT solution approaches existing in the literature. The proposed graph-based algorithms lead to a more competent mine scheduling optimisation expert system because the third-party MIP optimiser is no longer indispensable and random neighbourhood search is not necessary.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 43, January 2016, Pages 59–65
نویسندگان
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