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Hierarchical Approach to Integrated Planning of Industrial Gas Supply Chains

Lee, Y; Carrero-Parreno, A; Ramaswamy, S; Pinto, JM; Papageorgiou, LG; (2021) Hierarchical Approach to Integrated Planning of Industrial Gas Supply Chains. Industrial & Engineering Chemistry Research , 60 (14) pp. 5207-5219. 10.1021/acs.iecr.0c06289. Green open access

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Abstract

In this article, an optimization-based framework is proposed for integrated production and distribution planning of industrial gas supply chains. The main goal is to minimize the overall cost, which is composed of raw material, product sourced from external suppliers, production, truck, and rail-car costs, while satisfying customer demands. The overall problem is formulated as a mixed-integer linear programming (MILP) model while a two-phase hierarchical solution strategy is developed to solve the resulting optimization problem efficiently. The first phase relies on truck scheduling decisions being relaxed, whereas the second phase solves the original model at reduced space by fixing product allocation as determined by phase one. Finally, an industrial-size case study is used to illustrate the applicability and efficiency of the proposed optimization framework.

Type: Article
Title: Hierarchical Approach to Integrated Planning of Industrial Gas Supply Chains
Open access status: An open access version is available from UCL Discovery
DOI: 10.1021/acs.iecr.0c06289
Publisher version: https://doi.org/10.1021/acs.iecr.0c06289
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Science & Technology, Technology, Engineering, Chemical, Engineering, DECOMPOSITION, MODEL, COORDINATION, OPTIMIZATION
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering
URI: https://discovery.ucl.ac.uk/id/eprint/10137901
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