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Supply Chain Planning at a Chemical Process Industry
Linköping University, Department of Mathematics, Optimization . Linköping University, The Institute of Technology.ORCID iD: 0000-0002-9881-4170
Linköping University, Department of Management and Engineering, Production Economics. Linköping University, The Institute of Technology.
Linköping University, Department of Management and Engineering. Linköping University, The Institute of Technology.
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, The Institute of Technology.
2013 (English)In: Proceedings for Decision Science Institute (DSI 2013), The 44th Annual Meeting, 2013, Decision Sciences Institute , 2013, 671895 - 1-671895 - 19 p.Conference paper (Other academic)
Abstract [en]

The purpose of this paper is to develop 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 margin, that is, the difference between the selling price and the cost of production, transportation, inventory carrying and outsourcing. 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. The results of a baseline scenario 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
Decision Sciences Institute , 2013. 671895 - 1-671895 - 19 p.
Keyword [en]
Process Industry, Supply Chain, Mixed Integer Programming, Optimization
National Category
Computational Mathematics
URN: urn:nbn:se:liu:diva-104616OAI: diva2:697971
44th Decision Sciences Institute (DSI) Annual Meeting, Baltimore, USA, November 16-19, 2013
Process Industry Centre (PIC) supported by the Swedish Foundation for Strategic Research (SSF)
Available from: 2014-02-19 Created: 2014-02-19 Last updated: 2015-02-25Bibliographically approved

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Quttineh, Nils-HassanLidestam, HeleneOlsson, Sven
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