Journal
CHEMICAL ENGINEERING SCIENCE
Volume 95, Issue -, Pages 1-11Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ces.2013.02.054
Keywords
Supply chain management; Mixed-integer linear programming; Risk management; Multi-objective optimization; Life cycle assessment; Optimization under uncertainty
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Funding
- Spanish Ministry of Education and Science [ENE2011-28269-C03-03, ENE2011-22722, DPI2012-37154-C02-02, CTQ2009-14420-C02, CTQ2012-37039-C02]
- Programa DRAC de la Xarxa Vives d'Universitats
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In this work, we analyze the effect of demand uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear program (MILP) with the unique feature of incorporating explicitly the demand uncertainty using scenarios with given probability of occurrence. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact. (c) 2013 Elsevier Ltd. All rights reserved.
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