Ant Colony Algorithm Applied for Optimizing TFT-LCD Material Planning

• Main Authors: YunChien Chang, 章允建
• Other Authors: ChaoChang Chiu
• Format: Others
• Language: zh-TW
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/72088110095600003247

碩士 === 元智大學 === 資訊管理研究所 === 93 === TFT-LCD is now on developing and it is one of the focal industries in Taiwan. Generation technology has advanced all the time. In order to reduce the unit cost, the TFT-LCD industries need to invest much money in inventing new technology, and expanding factory building, therefore it must take orders in mass production to fill up the cost, and then to earn profits. In the material planning process of module process, planning good or not will influence the quantity of finished products. For this reason, we need a decision model to make TFT-LCD material planning optimal which enables the quantity of production more under much restriction. Today, the decision model in the TFT-LCD industries is APS, but it still insufficient. Our research will be based on Ant Colony Optimization algorithm (ACO) to develop a optimal decision model in planning material, and use Taguchi Method in parameters design to make this model better. In the experiment, the computational results on test problems will be in comparison with Genetic Algorithm (GA) and greedy method, and then could solve the problem of material planning and allocation efficiently.