A Risk-Based Multi-criteria Decision Support System for Sustainable Development in the Textile Supply Chain

  • Besoa Rabenasolo
  • Xianyi Zeng
Part of the Intelligent Systems Reference Library book series (ISRL, volume 33)


The modern textile/clothing industry is facing to a great number of important challenges related to sustainability. These challenges include environmental disasters and hazards to human health caused by toxic materials, resource exhaustion (water, energy, raw materials), and social impacts caused by delocalization, counterfeiting and other elements. In this context, in order to guarantee the development of the textile/clothing industry in a sustainable and optimal way when developing or producing new textile products, industrial companies need to optimize their production organization by minimizing risks occurring not only at the level of materials and processes but also in the whole international textile supply chain. In this chapter, we propose a risk-based multi-criteria decision support system for evaluating risks of different textile materials and the corresponding suppliers using the criteria of sustainable development (environment protection, recycling capacity, energy saving, human health and safety, and social impacts). Some evaluation criteria have been normalized by recognized international organizations. A method of data aggregation with multiple fuzzy criteria is applied in order to select the most appropriate textile material and its supplier. A new method combining expert knowledge on enterprise strategy and sensitivity criteria will be used for determining the linguistic weights of these fuzzy criteria. In this decision support system, the aggregated evaluation index takes into account the criteria of sustainable development and the specific application context as well as company strategies on the management of its supply chain.


Supply Chain Textile Material Evaluation Indicator Supply Chain Network Social Life Cycle Assessment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Besoa Rabenasolo
    • 1
    • 2
  • Xianyi Zeng
    • 1
    • 2
  1. 1.Ecole Nationale Supérieure des Arts et Industries TextilesRoubaixFrance
  2. 2.University of Lille Nord de FranceLilleFrance

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