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Method production scheduling using a comparison of genetic algorithm and other general methods |
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| รหัสดีโอไอ | |
| Creator | Adul Phuk-in |
| Title | Method production scheduling using a comparison of genetic algorithm and other general methods |
| Publisher | Faculty of Engineering, Khon Kaen Univeristy |
| Publication Year | 2555 |
| Journal Title | KKU Engineering Journal |
| Journal Vol. | 39 |
| Journal No. | 1 |
| Page no. | 35-46 |
| Keyword | Job scheduling problem,Genetic algorithm method |
| ISSN | 0125-8573 |
| Abstract | The goal of this study is to create the highest efficiency production work schedule. The following methods were used to design and develop the program to solve the problems : first in-first out (FIFO), shortest processing time (SPT), longest processing time (LPT), early due date (EDD), and minimize slack. The researcher had developed the genetic algorithm (GA) method which is the holistic method used for comparing the production scheduling outcome. Efficiency of the genetic algorithm was examined by designing a factorial 23 test for finding an appropriate parameter value using anova method. It was found that the appropriate value of the crossover, mutation, population size, and generation were equal to 1, 0.1, 100, and 50, respectively. This helped create a highest efficiency in the management of work schedule. With regards to 4 problems in the management of work schedule testing of the mental alloyed factory, it was found that the GA and LPT methods could provide the best work value. Based on the examining of problems in the production scheduling for 13 tasks of 3 task stations, problems in 23 task of 5 task stations, and problems in 27 tasks of 4 task stations, the value finding was found at a lower bound. In the case of problems in 27 tasks of 5 task stations, the NP-Hard problem was found. The GA method could provide the best work value, making the mental alloyed factory has alternatives for the production scheduling. Besides, it could be employed for an increase of the efficiency in the operation of this factory. |
