{"title":"A simulated annealing based stochastic long-term production scheduling of open-pit mines with stockpiling under grade uncertainty","authors":"Abid Ali Khan Danish, Asif Khan, Khan Muhammad","doi":"10.1080/17480930.2022.2140543","DOIUrl":null,"url":null,"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.","PeriodicalId":49180,"journal":{"name":"International Journal of Mining Reclamation and Environment","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2022-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Mining Reclamation and Environment","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/17480930.2022.2140543","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
The International Journal of Mining, Reclamation and Environment published research on mining and environmental technology engineering relating to metalliferous deposits, coal, oil sands, and industrial minerals.
We welcome environmental mining research papers that explore:
-Mining environmental impact assessment and permitting-
Mining and processing technologies-
Mining waste management and waste minimization practices in mining-
Mine site closure-
Mining decommissioning and reclamation-
Acid mine drainage.
The International Journal of Mining, Reclamation and Environment welcomes mining research papers that explore:
-Design of surface and underground mines (economics, geotechnical, production scheduling, ventilation)-
Mine planning and optimization-
Mining geostatics-
Mine drilling and blasting technologies-
Mining material handling systems-
Mine equipment