Cut order planning (COP) plays a significant role in managing the cost of materials. COP seeks to minimize the total manufacturing costs by developing feasible cutting order plans with respect to material, machine and labour. In this chapter, a genetic optimized decision-making model using adaptive evolutionary strategies is devised for COP. Four sets of real production data were collected to validate the proposed method. The experimental results demonstrate that the proposed method can reduce both the material costs and the production of additional garments while satisfying time constraints. Although the total operation time used is longer than that using industrial practice, this is outweighed by the benefits of reduction in fabric cost and extra garments.
|Title of host publication||Optimizing Decision Making in the Apparel Supply Chain Using Artificial Intelligence (AI)|
|Subtitle of host publication||From Production to Retail|
|Number of pages||25|
|Publication status||Published - 1 Jan 2013|
- Evolutionary strategies
- Resource utilization
ASJC Scopus subject areas