TY - JOUR
T1 - A stochastic approach for integrated production and distribution planning in dairy supply chains
AU - Guarnaschelli, Armando
AU - Salomone, Héctor Enrique
AU - Méndez, Carlos A.
N1 - Publisher Copyright:
© 2020
PY - 2020/9/2
Y1 - 2020/9/2
N2 - This work addresses production and distribution planning for a real-world dairy supply chain. The planning model accounts for the production and distribution of Cheese, Yogurt, Powdered Milk and UHT milk products across a two-echelon Supply Chain. This task is undermined by the inherent variability of raw materials and finished products demand. The integrated production and distribution planning methodology introduced is based on a two-stage stochastic mixed integer linear programming formulation. In real-world settings the number of scenarios grows substantially; thus, a scenario reduction strategy based on clustering techniques is given. A decomposition and solving strategy is also introduced and applied to a real-world case study. This study showed that the value of the stochastic solution might rise to 21.1% above the deterministic solution. This indicates the importance of considering uncertainty for dairy production and distribution. Besides, different-size instances are tested to study the scalability of the solution approach.
AB - This work addresses production and distribution planning for a real-world dairy supply chain. The planning model accounts for the production and distribution of Cheese, Yogurt, Powdered Milk and UHT milk products across a two-echelon Supply Chain. This task is undermined by the inherent variability of raw materials and finished products demand. The integrated production and distribution planning methodology introduced is based on a two-stage stochastic mixed integer linear programming formulation. In real-world settings the number of scenarios grows substantially; thus, a scenario reduction strategy based on clustering techniques is given. A decomposition and solving strategy is also introduced and applied to a real-world case study. This study showed that the value of the stochastic solution might rise to 21.1% above the deterministic solution. This indicates the importance of considering uncertainty for dairy production and distribution. Besides, different-size instances are tested to study the scalability of the solution approach.
KW - Dairy supply chains
KW - Production and Distribution Planning
KW - Stochastic programming
KW - Supply chain planning
UR - http://www.scopus.com/inward/record.url?scp=85086402274&partnerID=8YFLogxK
U2 - 10.1016/j.compchemeng.2020.106966
DO - 10.1016/j.compchemeng.2020.106966
M3 - Article
AN - SCOPUS:85086402274
SN - 0098-1354
VL - 140
JO - Computers and Chemical Engineering
JF - Computers and Chemical Engineering
M1 - 106966
ER -