Using job-based chromosomes with 1-tuple genes to develop meta-heuristic algorithms for DFJSP scheduling subject to maintenance

• Main Authors: Chang, Mu-Hsuan, 張慕萱
• Other Authors: Wu, Muh-Cherng
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/72106621164227574347

碩士 === 國立交通大學 === 工業工程與管理系所 === 101 === This thesis aims at solve the problem of distributed flexible job-shop subject to preventive maintenance (i.e., the DFJSP/PM problem). This scheduling problem is NP-hard, which contains four sub-decisions: (1) job-to-cell assignment, (2) operation-to-machine, (3) operation sequencing, and (4) preventive maintenance assignment. To solve this scheduling problem, this thesis develops two meta-heuristic algorithms based on a new solution representation (called Sjob-1t). Sjob-1t represents a solution by a sequence of generic jobs, which is composed of normal jobs and virtual PM jobs. Four heuristic rules are developed to decode the sequence of generic jobs to obtain the aforementioned four sub-decisions. The scheduling objecive is global makespan. Experiment results show that the two proposed algorithms both outperform prior algorithms in solving the DFJSP/PM problem.