Title :
A hybrid genetic approach for garment cutting in the clothing industry
Author :
Yeung, Leo Ho Wai ; Tang, Wallace K S
Author_Institution :
Dept. of Electron. Eng., City Univ. of Hong Kong, China
fDate :
6/1/2003 12:00:00 AM
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.
Keywords :
computational complexity; cutting; genetic algorithms; textile industry; NP-complete; clothing industry; garment cutting; genetic algorithm; heuristic algorithm; hybrid genetic approach; lowest-fit-left-aligned; searching domain; strip-packing problem; Clothing industry; Costs; Fabrics; Genetic algorithms; Helium; Heuristic algorithms; Manufacturing industries; Production; Productivity; Strips;
Journal_Title :
Industrial Electronics, IEEE Transactions on
DOI :
10.1109/TIE.2003.812285