Run-of-mine stockyard recovery scheduling and optimisation for multiple reclaimers

Hirad Assimi, Ben Koch, Chris Garcia, Markus Wagner, Frank Neumann

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1 Citation (Scopus)


Stockpiles are essential in the mining value chain, assisting in maximising value and production. Quality control of taken minerals from the stockpiles is a major concern for stockpile managers where failure to meet some requirements can lead to losing money. This problem was recently investigated using a single reclaimer, and basic assumptions. This study extends the approach to consider multiple reclaimers in preparing for short and long-term deliveries. The engagement of multiple reclaimers complicates the problem in terms of their interaction in preparing a delivery simultaneously and safety distancing of reclaimers. We also consider more realistic settings, such as handling different minerals with different types of reclaimers. We propose methods that construct a solution step by step to meet precedence constraints for all reclaimers in the stockyard. We study various instances of the problem using greedy algorithms, Ant Colony Optimisation (ACO), and propose an integrated local search method determining an efficient schedule. We fine-tune and compare the algorithms and show that the ACO combined with local search can yield efficient solutions.

Original languageEnglish
Title of host publicationProceedings of the 37th ACM/SIGAPP Symposium on Applied Computing, SAC 2022
EditorsHossain Shahriar
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Number of pages10
ISBN (Electronic)9781450387132
Publication statusPublished - 2022
Externally publishedYes
EventACM/SIGAPP Symposium on Applied Computing 2022 - Online, United States of America
Duration: 25 Apr 202229 Apr 2022
Conference number: 37th (Proceedings) (Website)


ConferenceACM/SIGAPP Symposium on Applied Computing 2022
Abbreviated titleSAC 2022
Country/TerritoryUnited States of America
Internet address


  • ant colony optimisation
  • greedy algorithm
  • iterative local search
  • parallel processing
  • stockpile

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