A six sigma based multi-objective optimization for machine grouping control in flexible cellular manufacturing systems with guide-path flexibility

2010 ◽  
Vol 41 (6) ◽  
pp. 865-873 ◽  
Author(s):  
Babak Shirazi ◽  
Hamed Fazlollahtabar ◽  
Iraj Mahdavi
Keyword(s):  
Six Sigma ◽  
Manufacturing Systems ◽  
Cellular Manufacturing ◽  
Multi Objective Optimization ◽  
Cellular Manufacturing Systems ◽  
Machine Grouping ◽  
Multi Objective

scholarly journals Modeling the Scheduling Problem in Cellular Manufacturing Systems Using Genetic Algorithm as an Efficient Meta-Heuristic Approach

2021 ◽  
Author(s):  
Amin Rezaeipanah ◽  
Musa Mojarad
Keyword(s):  
Genetic Algorithm ◽  
Manufacturing Systems ◽  
Cellular Manufacturing ◽  
Programming Model ◽  
Heuristic Method ◽  
Cell Formation ◽  
Mixed Integer ◽  
Test Problems ◽  
Cellular Manufacturing Systems ◽  
Machine Grouping

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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