Production planning and cell formation in dynamic virtual cellular manufacturing systems with worker flexibility

Author(s):  
Iraj Mahdavi ◽  
Amin Aalaei ◽  
Mohammad Mahdi Paydar ◽  
Maghsud Solimanpur
Author(s):  
Amin Rezaeipanah ◽  
Musa Mojarad

This paper presents a new, bi-criteria mixed-integer programming model for scheduling cells and pieces within each cell in a manufacturing cellular system. The objective of this model is to minimize the makespan and inter-cell movements simultaneously, while considering sequence-dependent cell setup times. In the CMS design and planning, three main steps must be considered, namely cell formation (i.e., piece families and machine grouping), inter and intra-cell layouts, and scheduling issue. Due to the fact that the Cellular Manufacturing Systems (CMS) problem is NP-Hard, a Genetic Algorithm (GA) as an efficient meta-heuristic method is proposed to solve such a hard problem. Finally, a number of test problems are solved to show the efficiency of the proposed GA and the related computational results are compared with the results obtained by the use of an optimization tool.


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