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Asian Journal of Industrial Engineering
  Year: 2010 | Volume: 2 | Issue: 1 | Page No.: 9-16
DOI: 10.3923/ajie.2010.9.16
 
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Deep Memory Greedy Search and Allocation of Job Shop Scheduling For Optimizing Shop Floor Performance
T. Hemamalini, A.N. Senthilvel and S. Somasundaram

Abstract:
The objective of this study was to improve shop floor performance through proper allocation of jobs in machines taking due time into consideration. In general, a constructive optimization method tries to give the best possible solution. On the other hand, an iterative process improvises an assumed initial solution, which may take a long time, since we do not know which would give the optimal solution in a stipulated time frame. Hence, we used the constructive method of optimization, barring the time taken to get the solution. A novel Deep Memory Greedy Search (DMGS) method is proposed to solve the above problem. The simulation run is conducted for different combination of jobs and machines with job processing time and results are illustrated. The performance charts are also plotted for visual analysis of the problem solving instances.
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How to cite this article:

T. Hemamalini, A.N. Senthilvel and S. Somasundaram, 2010. Deep Memory Greedy Search and Allocation of Job Shop Scheduling For Optimizing Shop Floor Performance. Asian Journal of Industrial Engineering, 2: 9-16.

DOI: 10.3923/ajie.2010.9.16

URL: https://scialert.net/abstract/?doi=ajie.2010.9.16

 
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