Applications of Genetic Algorithm to Optimize Unrelated Parallel Machines of Flexible Job-shop Scheduling Problem

• Main Authors: Hung-Te Tsai, 蔡宏德
• Other Authors: Tung-Kuan Liu
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/70431194889748468369

碩士 === 國立高雄第一科技大學 === 機械與自動化工程研究所 === 101 === In the face of a competitive manufacturing environment to reduce production costs, and effective use of production capacity and balance of factory load, hybrid production system configuration must be used. Unrelated parallel machines of flexible job shop is a hybrid production system. Therefore, this research will focus on Unrelated parallel machines of flexible job shop scheduling problem, proposed uses two different types of chromosome encoding, decimal coding and Integer coding combine with genetic algorithm, targeted at minimizing completion time for research. In this research, in order to verify the feasibility of using chromosome encoding method, divide the issue into different size and Writing program to compute its convergent curves, use well-known examples Brandimarte’s MK1 to MK10 proof the effectiveness of the proposed method.