A hybrid genetic approach for garment cutting in the clothing industry
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 449-455 |
| Journal / Publication | IEEE Transactions on Industrial Electronics |
| Volume | 50 |
| Issue number | 3 |
| Publication status | Published - Jun 2003 |
Link(s)
Abstract
A hybrid genetic approach is proposed for the cutting operation in the clothing industry. Garment cutting is a typical strip-packing problem, which is considered to be NP-complete. With a combination of genetic algorithm (GA) and a novel heuristic algorithm Lowest-Fit-Left-Aligned," the cutting problem is transformed into a simple permutation problem which can be effectively solved by the GA and the searching domain is greatly reduced. From the simulation results, it is demonstrated that the optimal results can be obtained in a reasonably short period of time.
Research Area(s)
- Clothing industry, Cutting problem, Genetic algorithm (GA), Heuristic algorithm
Citation Format(s)
A hybrid genetic approach for garment cutting in the clothing industry. / Yeung, Leo Ho Wai; Tang, Wallace K.S.
In: IEEE Transactions on Industrial Electronics, Vol. 50, No. 3, 06.2003, p. 449-455.
In: IEEE Transactions on Industrial Electronics, Vol. 50, No. 3, 06.2003, p. 449-455.
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
