Abstract
Traditional theories and principles on supply chains management (SCM) have implicitly assumed homogenous cultural environment characteristics across the entire supply chain (SC). In practice, however, such an assumption is too restrictive due to the dynamic and non-homogenous nature of organisational cultural attributes. By extending the evolutionary platform of cultural algorithms, we design an innovative multi-objective optimization model to test the null hypothesis – the SC’s performance is independent of its sub-chains cultural attributes. Simulation results suggest that the null hypothesis cannot be statistically accepted.
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Al-Mutawah, K., Lee, V., Cheung, Y. (2006). An Intelligent Algorithm for Modeling and Optimizing Dynamic Supply Chains Complexity. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing. ICIC 2006. Lecture Notes in Computer Science, vol 4113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816157_118
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DOI: https://doi.org/10.1007/11816157_118
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37271-4
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