scholarly journals Production Scheduling of Open Pit Mine Using Sequential Branch-and-Cut and Longest Path Algorithm: An Application from an African Copper Mine

2020 ◽  
Vol 53 (5) ◽  
pp. 629-636
Author(s):  
Devendra Joshi ◽  
Susanta Kumar Satpathy

Open pit mine production scheduling assigns mining blocks in different production periods for maximising profits after satisfying geotechnical and operational constraints. In this paper, two Open pit mine production scheduling models were applied in an African copper deposit. The first model is a traditional model with more tight resource constraints; the second model is a more robust model where resource constraints are relaxed by penalizing the objective function. Both the models were solved using two step algorithms: (a) year wise production scheduling using a sequential branch-and-cut algorithm; and (b) an iterative longest path algorithm to improve the solution generated from branch-and-cut. Results demonstrated that due to the tight constraints in Model 1, the optimizer was unable to generate a feasible solution after the first period, therefore the lower limit metal production constraint was eliminated to generate a feasible solution; however, Model 2 was able to generate a feasible solution for all periods. Results show that both the models generated nearly the same amount of ore, waste, metal content, and mine life. Model 2 generates relatively more net present value as compared to Model 1, whereas, the computational time required for solving the scheduling problem is relatively less for Model 1 than for Model 2.

Mining ◽  
2022 ◽  
Vol 2 (1) ◽  
pp. 32-51
Author(s):  
Devendra Joshi ◽  
Amol Paithankar ◽  
Snehamoy Chatterjee ◽  
Sk Md Equeenuddin

Open pit mine production scheduling is a computationally expensive large-scale mixed-integer linear programming problem. This research develops a computationally efficient algorithm to solve open pit production scheduling problems under uncertain geological parameters. The proposed solution approach for production scheduling is a two-stage process. The stochastic production scheduling problem is iteratively solved in the first stage after relaxing resource constraints using a parametric graph closure algorithm. Finally, the branch-and-cut algorithm is applied to respect the resource constraints, which might be violated during the first stage of the algorithm. Six small-scale production scheduling problems from iron and copper mines were used to validate the proposed stochastic production scheduling model. The results demonstrated that the proposed method could significantly improve the computational time with a reasonable optimality gap (the maximum gap is 4%). In addition, the proposed stochastic method is tested using industrial-scale copper data and compared with its deterministic model. The results show that the net present value for the stochastic model improved by 6% compared to the deterministic model.


2020 ◽  
Vol 27 (9) ◽  
pp. 2479-2493
Author(s):  
Kamyar Tolouei ◽  
Ehsan Moosavi ◽  
Amir Hossein Bangian Tabrizi ◽  
Peyman Afzal ◽  
Abbas Aghajani Bazzazi

2021 ◽  
Vol 71 ◽  
pp. 102016
Author(s):  
Abid Ali Khan Danish ◽  
Asif Khan ◽  
Khan Muhammad ◽  
Waqas Ahmad ◽  
Saad Salman

2017 ◽  
Vol 260 (1) ◽  
pp. 212-221 ◽  
Author(s):  
Eduardo Moreno ◽  
Mojtaba Rezakhah ◽  
Alexandra Newman ◽  
Felipe Ferreira

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