Hybrid Genetic Algorithms for Operation Scheduling
碩士 === 輔仁大學 === 管理學研究所 === 93 === Efficiency of produce is relative with scheduling. In economy of scale, the scheduling gets more attention with the increase of jobs. In actual, the work often needs more than one workshop. So that, the two-machine scheduling is important. The nature of the many sch...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2006
|
| Online Access: | http://ndltd.ncl.edu.tw/handle/34341297694506427265 |
| Summary: | 碩士 === 輔仁大學 === 管理學研究所 === 93 === Efficiency of produce is relative with scheduling. In economy of scale, the scheduling gets more attention with the increase of jobs.
In actual, the work often needs more than one workshop. So that, the two-machine scheduling is important.
The nature of the many scheduling problems is NP-hard. Scholars had used genetic algorithms to search the approximate optimum solution and had studied the special case of two-machine flowshop. For example: the relationship of the processing time of the different jobs.
This thesis directs at special case of the single performance measure of the two-machine flowshop and genetic algorithms. We tried to combine with special case and genetic algorithms in order to improve the efficiency of genetic algorithms.
The result showed that hybrid genetic algorithms are better than tradition genetic algorithms whether in the improvement of the optimum solution or speed.
|
|---|