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In this work, evolutionary algorithm and LM techniques are deployed simultaneously for optimal design of both connectivity configuration and associated coefficients of each candidate solution in the evolving population combination. However, use of singular value decomposition technique with LM is considered as a novel method to overcome the problem of initial guess, which is presented for the first time in this research. In order to illustrate the benefits of the proposed algorithm, it has been applied in a Malaysian manufacturing company for forecasting in inventory control. Moreover, a comparison between the basic GMDH algorithm and the enhanced GMDH algorithm is made, and the results show that the accuracy of the proposed method is considerably high with reasonable reduction in processing time. Therefore, the enhanced GMDH method can be used to replace old techniques in an inventory control system to generate a structure when it is applied to a Kanban setting in the just in time system.<\/jats:p>","DOI":"10.1017\/s0890060413000358","type":"journal-article","created":{"date-parts":[[2013,6,13]],"date-time":"2013-06-13T07:56:36Z","timestamp":1371110196000},"page":"377-385","source":"Crossref","is-referenced-by-count":1,"title":["Enhancing group method of data handling type modeling for nonlinear systems in inventory control"],"prefix":"10.1017","volume":"27","author":[{"given":"Maryam","family":"Pournasir","sequence":"first","affiliation":[]},{"given":"Md. 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Systems, Man, and Cybernetics, October 11\u201314."},{"key":"S0890060413000358_ref36","doi-asserted-by":"crossref","first-page":"1080","DOI":"10.1007\/s00170-007-1296-1","article-title":"Modeling tool wear in end-milling using enhanced GMDH learning networks","volume":"39","author":"Buryan","year":"2008","journal-title":"International Journal of Advanced Manufacturing Technology"},{"key":"S0890060413000358_ref37","doi-asserted-by":"publisher","DOI":"10.1016\/S0031-3203(03)00192-4"},{"key":"S0890060413000358_ref6","unstructured":"Fan J.Y. , & Yuan Y.X. (2001). On the Convergence of a New Levenberg\u2013Marquardt Method, Report No. 005. 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