A genetic algorithm for facility layout problems of different manufacturing environments

2004 ◽  
Vol 47 (2-3) ◽  
pp. 233-246 ◽  
Author(s):  
M. Adel El-Baz
Keyword(s):  
Genetic Algorithm ◽  
Facility Layout ◽  
Manufacturing Environments

A robust approach to design a single facility layout plan in dynamic manufacturing environments using a permutation-based genetic algorithm

2016 ◽  
Vol 230 (12) ◽  
pp. 2264-2274 ◽  
Author(s):  
Forough Zarea Fazlelahi ◽  
Mehrdokht Pournader ◽  
Mohsen Gharakhani ◽  
Seyed Jafar Sadjadi
Keyword(s):  
Genetic Algorithm ◽  
Large Scale ◽  
Heuristic Algorithms ◽  
Facility Layout ◽  
Robust Approach ◽  
The Past ◽  
Mixed Genetic Algorithm ◽  
Manufacturing Environments ◽  
Conventional Genetic Algorithm ◽  
Single Facility

During the past few decades, developing efficient methods to solve dynamic facility layout problems has been focused on significantly by practitioners and researchers. More specifically meta-heuristic algorithms, especially genetic algorithm, have been proven to be increasingly helpful to generate sub-optimal solutions for large-scale dynamic facility layout problems. Nevertheless, the uncertainty of the manufacturing factors in addition to the scale of the layout problem calls for a mixed genetic algorithm–robust approach that could provide a single unlimited layout design. The present research aims to devise a customized permutation-based robust genetic algorithm in dynamic manufacturing environments that is expected to be generating a unique robust layout for all the manufacturing periods. The numerical outcomes of the proposed robust genetic algorithm indicate significant cost improvements compared to the conventional genetic algorithm methods and a selective number of other heuristic and meta-heuristic techniques.

Research on the Facilities Layout Planning in MTO Manufacturing Industry Based on Genetic Algorithm

2013 ◽  
Vol 842 ◽  
pp. 695-702
Author(s):  
Ying Wang ◽  
You Rong Li ◽  
Yu Qiong Zhou
Keyword(s):  
Genetic Algorithm ◽  
Manufacturing Industry ◽  
Design Method ◽  
Facility Layout ◽  
Optimization Method ◽  
Market Demand ◽  
Layout Planning ◽  
Manufacturing Enterprises ◽  
Make To Order ◽  
Systematic Layout Planning

To enlarge production to meet the market demand, its nessasery to improve the present facility layout for MTO (Make-To-Order) manufacturing enterprises. This paper tries to design a optimization method based on genetic algorithm for the facility layout of MTO enterprises. Firstly, SLP (systematic layout planning) was applied to analyze the material and non-material flow interrelation of the workshop. Secondly, a relatively optimum layout was determined after using fuzzy hierarchy estimation to evaluate the schemes. Then the scheme was optimized with genetic algorithm. The result shows that the optimized logistics transport load is obviously less than before. This design method based on genetic algorithm (GA) is proved feasible and effective in the optimization of facility layout.

An Improved Genetic Algorithm for Digital Facility Layout Optimization Oriented Multi-Species and Variable-Batch Production Mode

2013 ◽  
Vol 694-697 ◽  
pp. 3632-3635
Author(s):  
Dao Guo Li ◽  
Zhao Xia Chen
Keyword(s):  
Genetic Algorithm ◽  
Facility Layout ◽  
Optimal Solution ◽  
Convergence Speed ◽  
Improved Genetic Algorithm ◽  
Layout Problem ◽  
Batch Production ◽  
Production Mode ◽  
Slow Convergence ◽  
Weak Points

When solving facility layout problem for the digital workshop to optimize the production, the traditional genetic algorithm has its flaws with slow convergence speed and that the accuracy of the optimal solution is not ideal. This paper analyzes those weak points and proposed an improved genetic algorithm according to the characteristics of multi-species and variable-batch production mode. The proposed approach improved the convergence speed and the accuracy of the optimal solution. The presented model of GA also has been tested and verified by simulation.

A genetic algorithm for facility layout problems

1998 ◽  
Vol 11 (1-2) ◽  
pp. 113-127 ◽  
Author(s):  
K.L. Mak ◽  
Y.S. Wong ◽  
F.T.S. Chan
Keyword(s):  
Genetic Algorithm ◽  
Facility Layout
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