NEDec 23, 2021

Run-of-Mine Stockyard Recovery Scheduling and Optimisation for Multiple Reclaimers

arXiv:2112.12294v1
Originality Incremental advance
AI Analysis

This work addresses a domain-specific optimization problem for mining stockyard managers, representing an incremental extension from single to multiple reclaimers.

The study tackled the problem of scheduling multiple reclaimers in a mining stockyard to meet delivery requirements, proposing an integrated Ant Colony Optimization with local search that yields efficient solutions.

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.

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