A neuro-genetic approach to design and planning of a manufacturing cell

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dc.contributor.author	Cakar, Tarik
dc.contributor.author	Yildirim, Mehmet Bayram
dc.contributor.author	Barut, Mehmet
dc.date.accessioned	2011-03-22T20:29:33Z
dc.date.available	2011-03-22T20:29:33Z
dc.date.issued	2005
dc.identifier.issn	0956-5515
dc.identifier.uri	http://hdl.handle.net/10057/3447
dc.identifier.uri	http://dx.doi.org/10.1007/s10845-005-1657-2
dc.description	The full text of this article is not available on SOAR. WSU users can access the article via commercial databases licensed by University Libraries: http://libcat.wichita.edu/vwebv/holdingsInfo?bibId=1379503
dc.description.abstract	In this paper, we propose a neuro-genetic decision support system coupled with simulation to design a job shop manufacturing system by achieving predetermined values of targeted performance measures such as flow time, number of tardy jobs, total tardiness and machine utilization at each work center. When a manufacturing system is designed, the management has to make decisions on the availability of resources or capacity, in our setting, the number of identical machines in each work station and the dispatching rule to be utilized in the shop floor to achieve performance values desired. Four different priority rules are used as Earliest due date (EDD), Shortest Processing Time (SPT), Critical ratio (CR) and First Come First Serve (FCFS). In reaching the final decision, design alternatives obtained from the proposed system are evaluated in terms of performance measures. An illustrative example is provided to explain the procedure.	en_US
dc.language.iso	en_US	en_US
dc.publisher	Springer Verlag	en_US
dc.relation.ispartofseries	Journal of Intelligent Manufacturing, 16, 453–462, 2005;
dc.subject	Resource allocation	en_US
dc.subject	Dispatching rule	en_US
dc.subject	Neuro-genetic	en_US
dc.subject	Hybrid scheduling	en_US
dc.title	A neuro-genetic approach to design and planning of a manufacturing cell	en_US
dc.type	Article	en_US