Affiliation:
1. Technical University of Kosice
Abstract
One of the complexity metrics that contribute towards determination of the overall complexity of supply chains is based on so called static complexity. In this article, we firstly present an architectural framework for supply chain networks. Subsequently, selected complexity indicators based on Axiomatic Design theory and Boltzmann entropy are applied. The indicators used are benchmarked based on computational experiments. Finally, relevant conclusions are formulated.
Publisher
Trans Tech Publications, Ltd.
Reference20 articles.
1. N. Aissaoui, M. Haouari, E. Hassini, Supplier selection and order lot sizing modeling: A review, Comput. Oper. Res. 34 (2007) 3516-3540.
2. S. Bednar, V. Modrak, Mass Customization and its Impact on Assembly Process' Complexity, International Journal for Quality Research 8 (2014) 417-430.
3. D. Aprile, A.C. Garavelli, I. Giannoccaro, Operation planning and flexibility in a supply chain, Journal of Production Planning and Control 16 (2005) 21-31.
4. T.F. Liang, H.W. Cheng, Application of fuzzy sets to manufacturing/distribution planning decisions with multi-product and multi-time period in supply chains, Expert Syst. Appl. 36 (2009) 3367-3377.
5. W. ElMaraghy, H. ElMaraghy, T. Tomiyama, L. Monostori, Complexity in engineering design and manufacturing, CIRP Ann. Manuf. Techn. 61(2012) 793-814.