Taxonomy of Manufacturing Flexibility at Manufacturing Companies Using Imperialist Competitive Algorithms, Support Vector Machines and Hierarchical Cluster Analysis


  • M. Khoobiyan Department of Management, Ferdowsi University of Mashhad, Mashhad, Iran
  • A. Pooya Department of Management, Ferdowsi University of Mashhad, Mashhad, Iran
  • A. Tavakkoli Department of Management, Ferdowsi University of Mashhad, Mashhad, Iran
  • F. Rahimnia Department of Management, Ferdowsi University of Mashhad, Mashhad, Iran
Volume: 7 | Issue: 2 | Pages: 1559-1566 | April 2017 |


Manufacturing flexibility is a multidimensional concept and manufacturing companies act differently in using these dimensions. The purpose of this study is to investigate taxonomy and identify dominant groups of manufacturing flexibility. Dimensions of manufacturing flexibility are extracted by content analysis of literature and expert judgements. Manufacturing flexibility was measured by using a questionnaire developed to survey managers of manufacturing companies. The sample size was set at 379. To identify dominant groups of flexibility based on dimensions of flexibility determined, Hierarchical Cluster Analysis (HCA), Imperialist Competitive Algorithms (ICAs) and Support Vector Machines (SVMs) were used by cluster validity indices. The best algorithm for clustering was SVMs with three clusters, designated as leading delivery-based flexibility, frugal flexibility and sufficient plan-based flexibility.


manufacturing flexibility, taxonomy, dominant groups, hierarchical cluster analysis, support vector machines, imperialist competitive algorithm


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How to Cite

M. Khoobiyan, A. Pooya, A. Tavakkoli, and F. Rahimnia, “Taxonomy of Manufacturing Flexibility at Manufacturing Companies Using Imperialist Competitive Algorithms, Support Vector Machines and Hierarchical Cluster Analysis”, Eng. Technol. Appl. Sci. Res., vol. 7, no. 2, pp. 1559–1566, Apr. 2017.


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