Stochastic production scheduling to meet demand forecasts

2002 ◽  
Author(s):  
J.G. Schneider ◽  
J.A. Boyan ◽  
A.W. Moore
Keyword(s):  
Production Scheduling ◽  
Stochastic Production ◽  
Stochastic Production Scheduling ◽  
Demand Forecasts

scholarly journals Integrated Parametric Graph Closure and Branch-and-Cut Algorithm for Open Pit Mine Scheduling under Uncertainty

Mining ◽  
2022 ◽  
Vol 2 (1) ◽  
pp. 32-51
Author(s):  
Devendra Joshi ◽  
Amol Paithankar ◽  
Snehamoy Chatterjee ◽  
Sk Md Equeenuddin
Keyword(s):  
Production Scheduling ◽  
Resource Constraints ◽  
Deterministic Model ◽  
Open Pit Mine ◽  
Branch And Cut ◽  
Open Pit ◽  
Computational Time ◽  
Scheduling Problems ◽  
Stochastic Production ◽  
Stochastic Production Scheduling

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.

Penjadwalan Produksi Menggunakan Metode Simulated Annealing pada Unit Produksi Daun Pintu di PT. ML

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Rosnani Ginting ◽  
Chairul Rahmadsyah Manik
Keyword(s):  
Simulated Annealing ◽  
Problem Solving ◽  
Production Scheduling ◽  
Production Control ◽  
Delivery Time ◽  
Production Schedule ◽  
A Company ◽  
Predetermined Time ◽  
Factory Floor

Penjadwalan merupakan aspek yang sangat penting karena didalamnya terdapat elemen perencanaan dan pengendalian produksi bagi suatu perusahaan yang dapat mengirim barang sesuai dengan waktu yang telah ditentukan, untuk memperoleh waktu total penyelesaian yang minimum. Masalah utama yang dihadapi oleh PT. ML adalah keterlambatan penyelesaian order yang mempengaruhi delivery time ke tangan costumer karena pelaksanaan penjadwalan produksi dilantai pabrik belum menghasilkan makespan yang sesuai dengan order yang ada. Oleh kaena itu dituntut untuk mencari solusi pemecahan masalah optimal dalam penentuan jadwal produksi untuk meminimisasi total waktu penyelessaian (makespan) semua order. Dalam penelitian ini, penjadwalan menggunakan metode Simulated Annealing (SA) diharapkan dapat menghasilkan waktu total penyelesaian lebih cepat dari penjadwalan yang ada pada perusahaan.   Scheduling is a very important aspect because in it there are elements of planning and production control for a company that can send goods in accordance with a predetermined time, to obtain a minimum total time of completion. The main problem faced by PT. ML is the delay in completing orders that affect delivery time to customer because the implementation of production scheduling on the factory floor has not produced the makespan that matches the existing order. Therefore, it is required to find optimal problem solving solutions in determining the production schedule to minimize the total time of elimination (makespan) of all orders. In this study, scheduling using the Simulated Annealing (SA) method is expected to produce a total time of completion faster than the existing scheduling in the company.

Refinery production scheduling toward Industry 4.0

2018 ◽  
Vol 0 (0) ◽  
pp. 0 ◽  
Author(s):  
Marcel JOLY ◽  
Darci ODLOAK ◽  
MarioY. MIYAKE ◽  
Brenno C. MENEZES ◽  
Jeffrey D. KELLY
Keyword(s):  
Production Scheduling ◽  
Industry 4.0 ◽  
Refinery Production
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