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Using rolling horizon techniques in the planning process for a chemical process industry
Linköping University, Department of Mathematics, Optimization . Linköping University, The Institute of Technology. (Division of Optimization)ORCID iD: 0000-0002-9881-4170
Linköping University, Department of Management and Engineering, Production Economics. Linköping University, The Institute of Technology.
2014 (English)In: Pre-Prints, Vol.1, 18th International Working Seminars on Production Economics, Innsbruck, Austria, February 2014., 2014, 381-393 p.Conference paper (Refereed)
Abstract [en]

We present a mathematical optimization model that can be used as a decision support tool for the supply chain planning at Perstorp Oxo AB, a global company in the process industry. At their site in Stenungsund, Perstorp Oxo AB produce chemicals to customers in a variety of branches and for further refinement at other Perstorp sites in Gent, Castellanza and Perstorp. The customers are mainly in branches such as food and feed, leather and textile, plastic and safety glass production. Since Perstorp Oxo sells products to customers worldwide, two large inventory facilities are located in Antwerp (Belgium) and Tees (United Kingdom) for five product types each and two smaller facilities in Philadelphia (USA) and Aveiro (Portugal) for one type respectively. The developed model is a mixed-integer linear program, where the objective function maximizes the profit. A solution to the model shows the quantities to be transported between the different sites, production rates, inventory levels, setups and purchases from external suppliers, each with its respective cost. Based on actual sales data from Perstorp Oxo AB, we use rolling horizon techniques to simulate how customer demands vary over a time horizon of one year, and show that our optimization model is able to find feasible and profitable production plans. The results show that there is a potential to increase profit margin by using a decision support tool based on an optimization model.

Place, publisher, year, edition, pages
2014. 381-393 p.
Keyword [en]
Supply Chain, Mixed Integer Programming, Optimization, Process Industry.
National Category
Mathematics Computational Mathematics
URN: urn:nbn:se:liu:diva-114509OAI: diva2:790509
18th International Working Seminars on Production Economics, Innsbruck, Austria, February 2014.
Process Industry Centre (PIC)
Swedish Foundation for Strategic Research
Available from: 2015-02-24 Created: 2015-02-24 Last updated: 2015-06-29Bibliographically approved

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Quttineh, Nils-HassanLidestam, Helene
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