A simulated annealing based stochastic long-term production scheduling of open-pit mines with stockpiling under grade uncertainty. Issue 1 (2nd January 2023)

• Record Type: Journal Article
• Authors: Danish, Abid Ali Khan; Khan, Asif; Muhammad, Khan
• Is Part Of: International journal of mining, reclamation and environment. Volume 37:Issue 1(2023)
• Page Start: 43
• Page End: 65
• Publication Date: 2023-01-02
• Subjects: Metaheuristics (simulated annealing) -- long-term production scheduling -- geological uncertainty -- stockpile option -- stochastic optimization -- two-stage stochastic optimisation; Mining engineering -- Periodicals; Mineral industries -- Environmental aspects -- Periodicals; Abandoned mined lands reclamation -- Periodicals; 622.292
• DOI: 10.1080/17480930.2022.2140543
• Languages: English
• ISSNs: 1748-0930

Abstract

ABSTRACT: This research presents a new Simulated Annealing based stochastic optimisation algorithm to integrate geological uncertainty into the optimization process through multiple equiprobable simulated realisations of an orebody while considering stockpiling options and other relevant constraints. The stockpiling option is included, increasing the chances of processing high-grade and most certain ore blocks in early periods. The efficiency of the proposed algorithm in creating a single good enough production schedule that minimises the risk of deviation from production targets while maximising the net present value of the operation is demonstrated through three case studies, i.e. case A with 2448 blocks, B with 6, 578 and C with 10, 810 blocks. The comparison of results with the two-stage stochastic model reveals that the proposed methodology reduces the risk of production deviation to a minimal and provides a near-optimal solution with an optimality gap of 3.53, −0.87, and 8.19% for cases A, B, and C within a reasonable amount of time.