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Maestría en Ingeniería / Estudiantes Skip Navigation Linksenvironmental-improvement Proyectos realizados / Environmental improvement of operating supply chains: A multi-objective approach for the cement industry

EAFITProgramasPosgradosMaestría en IngenieríaMaestría en Ingeniería / EstudiantesProyectos realizados / Environmental improvement of operating supply chains: A multi-objective approach for the cement industry

Proyectos realizados / Environmental improvement of operating supply chains: A multi-objective approach for the cement industry

Nora Cadavid Giraldo

​Abstract
Nowadays companies worldwide face a growing pressure to reduce the environmental impact of their manufacturing activities.  However, the strategies used to achieve this goal are not clearly defined because of their conflicting relations with financial outcomes.  In parallel, globalization trends imply that as companies  grow,  usually  through mergers and acquisitions,  their  supply  chains  become more complex.  The environmental improvement of these supply chains imply not only technical retrofit decisions aiming at adopting cleaner production technologies but also decisions regarding the structure of the supply chain itself.  Making these decisions becomes a difficult task because of the large number of variables involved, and the diversity of the interactions among them.  To tackle this problem, this research aims at providing a multi-objective solution approach for making technological retrofit decisions within an operating supply chain, so that both environmental and financial goals are best met.  The proposed solution approach is applied to the case of an operating cement supply chain in Colombia.  Several computational experiments were conducted,  obtained results demonstrates that the proposed model is an effective tool for multi-objective improvement decisions making, towards a more sustainable production process.


Keywords:
Sustainable supply chain management,  technological updating decision making,  en-terprise wide optimization, multi-objective optimization, mixed integer linear programming.