Short-Term Scheduling of Production Fleets in Underground Mines Using CP-Based LNS

Åstrand, Max; Johansson, Mikael; Feyzmahdavian, Hamid Reza

doi:10.1007/978-3-030-78230-6_23

Cited by 2 publications

(1 citation statement)

References 25 publications

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“…They also considered equipment movement time and proposed a simple neighborhood search strategy with a fixed neighborhood size based on constraint programming to study the scheduling problem of mining equipment in underground mines [18]. In addition, they also put forward a large neighborhood search strategy, based on constraint programming, that dynamically adjusts the size of the neighborhood to study the scheduling problem of mining equipment in underground mines, enabling the quick adjustment of the scheduling plan [19]. Feng et al [20] proposed a rescheduling optimization model of underground mine transportation equipment, considering equipment failure and adopting the wolf colony algorithm to optimize the solution.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Scheduling Model for Underground Metal Mines under Equipment Failure Conditions

Jia

Wang

et al. 2023

Sustainability

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Equipment failure is a common problem in mining operations, resulting in significant delays and reductions in production efficiency. To address this problem, this paper proposes a dynamic scheduling model for underground metal mines under equipment failure conditions. The model aims to minimize the impact of equipment failures on production operations while avoiding extensive equipment changes. A case study of the southeastern mining area of the Chambishi Copper Mine is presented to demonstrate the effectiveness of the proposed model. The initial plan was generated using the multi-equipment task assignment model for the horizontal stripe pre-cut mining method. After equipment breakdown, the proposed model was used to reschedule the initial plan. Then, a comparative analysis was carried out. The results show that the proposed model effectively reduces the impact of equipment failures on production operations and improves overall mining execution at a low management cost. In general, the proposed model can assist schedulers in allocating equipment, coping with the disturbing effects of equipment failure, and improving mine production efficiency.

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Section: Introductionmentioning

confidence: 99%

A Dynamic Scheduling Model for Underground Metal Mines under Equipment Failure Conditions

Jia

Wang

et al. 2023

Sustainability

View full text Add to dashboard Cite

show abstract

A Multi-Equipment Task Assignment Model for the Horizontal Stripe Pre-Cut Mining Method

Jia

Wang

et al. 2022

Sustainability

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This paper proposes a multi-equipment task assignment model for the horizontal stripe pre-cut mining method to address the problem of cooperative scheduling operation of multi-equipment in underground metal mines under complex constraints. The model is constructed with multiple objectives, including operation time, operational efficiency, equipment utilization rate, and ore grade fluctuation by considering the constraints of time, space, equipment, and processes. The NSGA-III algorithm is used to obtain the solution. The effectiveness of the algorithm is tested based on the actual data from the Chambishi Copper Mine. The results show that the average equipment utilization rate is 51.25%, and the average ore output efficiency is 278.71 tons/hour. The NSGA-III algorithm can quickly generate the optimal multi-equipment task assignment solution. The solution reduces the interference of manual experience and theoretically improves the actual operation of the mine.

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Short-Term Scheduling of Production Fleets in Underground Mines Using CP-Based LNS

Cited by 2 publications

References 25 publications

A Dynamic Scheduling Model for Underground Metal Mines under Equipment Failure Conditions

A Dynamic Scheduling Model for Underground Metal Mines under Equipment Failure Conditions

A Multi-Equipment Task Assignment Model for the Horizontal Stripe Pre-Cut Mining Method

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