کاربرد الگوریتم مرغابی در برنامه‌‌ریزی تولید بلندمدت معادن روباز

نوع مقاله : مقاله پژوهشی

نویسندگان

دانشکده مهندسی معدن، دانشگاه صنعتی امیرکبیر، تهران، ایران

چکیده

تعیین محدوده نهایی بهینه و برنامه‌‌ریزی تولید معدن همواره یکی از چالش‌‌های اصلی حوزه فعالیت‌‌های معدنی بوده است. این دو مسئله، تعیین‌‌کننده مولفه‌‌های موثر در معدنکاری و تصمیم‌‌گیری‌‌های خرد و کلان پروژه معدنی به‌‌ویژه برنامه‌‌ریزی تولید است. مساله برنامه‌‌ریزی تولید معادن روباز با استفاده از روش‌‌های دقیق و روش‌‌های هوش مصنوعی قابل محاسبه می‌‌باشد. روش‌‌های دقیق معمولا به نتیجه‌‌ای بهتر و بهینه خواهند رسید، اما در مسایل بزرگ با تعداد بلوک‌‌های زیاد ممکن است با زمان حل بسیار بالایی قادر به پاسخ‌‌گویی به مساله باشد. در این شرایط بهتر است از الگوریتم‌‌های هوش جمعی یا تکاملی برای تعیین محدوده نهایی و برنامه‌‌ریزی تولید استفاده کرد. بهینه‌‌سازی مساله برنامه‌‌ریزی تولید شبیه به مسایل بهینه‌‌سازی دیگر بوده و با استفاده از یک منطق الگوریتمی در نرم‌‌افزار متلب قابل حل هستند. در این تحقیق از الگوریتم کشتل در متلب برای بهینه‌‌سازی برنامه‌‌ریزی تولید استفاده شده است. ابتدا الگوریتم کشتل برای حل مساله دو بعدی و سه بعدی پیاده‌‌سازی شده و در نهایت معدن مس سونگون به عنوان مطالعه موردی انتخاب و نتایج حل مساله برنامه‌‌ریزی تولید با الگوریتم کشتل و نرم‌‌افزار NPV Scheduler مقایسه شده است. نتایج نشان می‌‌دهد که استفاده از الگوریتم کشتل در مسئله برنامه‌‌ریزی تولید اختلاف 1/8 درصدی با نرم افزار NPV Scheduler دارد. مقایسه الگوریتم کشتل با نتایج الگوریتم گرشون و برنامه‌‌ریزی پویا در برنامه‌‌ریزی تولید دوبعدی و مقایسه نتایج حاصله از الگوریتم کشتل با نرم‌‌افزار NPV Scheduler در مسائل سه بعدی نشان‌‌دهنده کارایی مناسب آن در حل این مسائل است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Application of Keshtel Algorithm for Long Term Production Planning in Open Pit Mines

نویسندگان [English]

  • Sajjad Rostamian
  • Majid Ataee-pour
  • Zeinab Jahanbani
Department of Mining Engineering, Amirkabir University of Technology, Tehran, Iran
چکیده [English]

Ultimate pit limit optimization and production mine planning have always been the main challenges in the field of mining activities. The production mine planning can be determined through accurate methods and artificial intelligence techniques. While exact methods provide better and optimal results, they may require significant time to answer the problem due to the large number of blocks involved. In such cases, it is more suitable to use collective algorithms or a planned approach to determine the production mine planning. Production mine planning is similar to other optimization problems that can be addressed using logical algorithms in MATLAB software. In this study, Keshtel's algorithm, implemented in MATLAB, is utilized to optimize the production mine planning. Initially, Keshtel's algorithm is employed to solve two-dimensional and three-dimensional problems. Subsequently, the Songun Copper Mine is chosen as a case study and the results of determining the production mine planning by Keshtel's algorithm are compared with the findings of NPV Scheduler software. The outcomes show that Keshtel's algorithm, used to determine the production mine planning of the Songun Copper Mine, differs by only 1.8% when compared to the NPV Scheduler software. Moreover, the comparison of Keshtel's algorithm with the results of Gershon in two-dimensional production mine planning, as well as the comparison with NPV Scheduler software in three-dimensional problems, demonstrates its efficiency in solving these issues effectively.

کلیدواژه‌ها [English]

  • Production Mine Planning
  • Optimization
  • Keshtel Algorithm
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