Multiobjective model for more sustainable fuel supply chains. A case study of the sugar cane industry in argentina

The objective of this work is to present a quantitative tool to support decision-making in the area of optimal design of supply chains (SC) for the combined production of sugar and ethanol. The problem is formulated as a multiobjective mixed-integer linear program that seeks to optimize simultaneously the economic and environmental performance of the production chain. The advantages of the approach presented are illustrated through its application to a case study, in which a trade-off exists between the economic and environmental performance of the network. Our method provides valuable insight into the problem and a guide to adopt more sustainable strategic alternatives in the design of SCs with embedded biorefineries.Fil: Mele, Fernando Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; ArgentinaFil: Kostin, Andrew M.. Universitat Rovira I Virgili; EspañaFil: Guillén Gosálbez, Gonzalo. Universitat Rovira I Virgili; EspañaFil: Jiménez, Laureano. Universitat Rovira I Virgili; Españ

Identifying key life cycle assessment metrics in the multiobjective design of bioethanol supply chains using a rigorous mixed-integer linear programming approach

The design of more sustainable bioethanol supply chains (SCs) has recently emerged as an active area of research. Most of the approaches presented so far have somehow a limited scope, as they focus on minimizing the emitted greenhouse gases as unique criterion, neglecting the damage caused in other impact categories. In this work, we address the multiobjective design of bioethanol SCs considering several life cycle assessment impacts. To overcome the numerical difficulties of dealing with several objective functions, we investigate the application of a rigorous mixed-integer linear programming-based dimensionality reduction method that minimizes the error of omitting objectives. The usefulness of this approach is tested through its application to the design of a bioethanol/sugar SC in Argentina, in which five environmental objectives are simultaneously optimized along with the net present value. The proposed method makes it possible to reduce the number of environmental indicators, thereby facilitating the calculation and analysis of the Pareto solutions.Fil: Kostin, Andrey M.. Universitat Rovira I Virgili; EspañaFil: Guillén Gosálbez, Gonzalo. Universitat Rovira I Virgili; EspañaFil: Mele, Fernando Daniel. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; ArgentinaFil: Jiménez, Laureano. Universitat Rovira I Virgili; Españ