TY - JOUR
T1 - A nationwide planning model for argon supply chains with coordinated production and distribution
AU - Neiro, Sergio M.S.
AU - Madan, Tarun
AU - Maravelias, Christos T.
AU - Pinto, José M.
N1 - Publisher Copyright: © 2024
PY - 2025/3
Y1 - 2025/3
N2 - In this work, we address a nationwide tactical planning for industrial gas supply chains, particularly argon. The proposed approaches follow as extensions of our previous work (Comp. & Chem. Eng., 161 (2022) 107778) in which a regional argon supply chain problem is addressed; in that work, both production and distribution could be represented in detail. Two different types of deliveries from the Air Separating Units (ASU) to customers, which involve single driver deliveries for short distance trips and sleeper team that require multiple days. The nationwide problem requires simplifications to keep the problem mathematically tractable, primarily the representation of production sites with different tier costs and the aggregation of customers in clusters. The regional problem addressed in our previous work is used as a benchmark case study for benchmarking. We then focus on a real-world problem that represents a nationwide argon supply chain. Despite the size of the models, near optimal solutions could be found in reasonable times. Finally, we highlight important features of the proposed approaches.
AB - In this work, we address a nationwide tactical planning for industrial gas supply chains, particularly argon. The proposed approaches follow as extensions of our previous work (Comp. & Chem. Eng., 161 (2022) 107778) in which a regional argon supply chain problem is addressed; in that work, both production and distribution could be represented in detail. Two different types of deliveries from the Air Separating Units (ASU) to customers, which involve single driver deliveries for short distance trips and sleeper team that require multiple days. The nationwide problem requires simplifications to keep the problem mathematically tractable, primarily the representation of production sites with different tier costs and the aggregation of customers in clusters. The regional problem addressed in our previous work is used as a benchmark case study for benchmarking. We then focus on a real-world problem that represents a nationwide argon supply chain. Despite the size of the models, near optimal solutions could be found in reasonable times. Finally, we highlight important features of the proposed approaches.
KW - Industrial gases
KW - Mixed-integer linear programming
KW - Supply chain optimization
UR - http://www.scopus.com/inward/record.url?scp=85211052169&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85211052169&partnerID=8YFLogxK
U2 - 10.1016/j.dche.2024.100201
DO - 10.1016/j.dche.2024.100201
M3 - Article
SN - 2772-5081
VL - 14
JO - Digital Chemical Engineering
JF - Digital Chemical Engineering
M1 - 100201
ER -