A Neural Network Clustering Method for the Part-Machine

• Main Authors: Shin-Jia Chen, 陳信嘉
• Other Authors: Chuen-Sheng Cheng
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/15418045690224840976

碩士 === 元智大學 === 工業工程研究所 === 81 === This research investigates the application of artificial neural network techniques to the part-machine grouping problem in GT. The neural network models considered in this research include three variations of Adaptive Resonance Theory (Carpenter- Grossberg''s Network, ART-1 and ART-2) and Self-Organizing MAP (SOM). Several enhancements to the neural network are proposed. Two performance measures, the number of exceptional parts and grouping efficiency, which are frequently used in the literature are used to compare the quality of solutions. An extensive comparison shows that the proposed algorithm outprforms existing techniques in terms of efficiency and effectiveness.