A mixed-integer programming strategy for liquid helium global supply chain planning

• Published in: Transportation research. Part E, Logistics and transportation review Vol. 110; pp. 168 - 188
• Main Authors: Malinowski, Ethan, Karwan, Mark H., Pinto, José M., Sun, Lei
• Format: Journal Article
• Language: English
• Published: Elsevier India Pvt Ltd 01.02.2018
• Subjects: Industrial gas supply chain; Mixed-integer programming; Rolling horizon; Supply chain analytics; Supply chain analytics; Industrial gas supply chain; Mixed-integer programming; Rolling horizon
• ISSN: 1366-5545; 1878-5794
• DOI: 10.1016/j.tre.2017.12.014

•The liquid helium global supply chain is modeled and solved.•A large-scale, discrete time, path-based integer program is proposed.•A rolling horizon approach is implemented and deemed necessary for reality.•The proposed model is tested using historical data from a helium industry business.•Major variable refinements result in optimal baseline solutions in 90 seconds. The global supply chain for liquid helium presents a complex structure due to increasing foreign demand, elaborate recovery techniques, and costly forms of distribution. Although the problem contains parallels to the liquid natural gas supply chain, supply requirements and problem-specific network constraints require a unique optimization model. We develop a large-scale, discrete time, path-based integer-programming model which solves optimally with CPLEX. Computational results implementing a rolling horizon structure and testing based on historical data are presented. A detailed sensitivity analysis demonstrates the effective use of our model, testing a variety of realistic parameter settings for the liquid helium supply chain.