Abstract
We propose an integrated genetic algorithm that can solve Job-oriented multi-objective FJSP (Flexible Job Shop Scheduling Problem) better. Scheduling model and job-oriented multi-objective algorithm for optimizing the solution of job-oriented multi-objective FJSP are proposed. We give a numerical simulation example, whose results are given in Tables 1 through 3 in the full paper and shown in Fig.2 of the full paper giving the Gantt chart of the best-compromise solution. These results show preliminarily that the proposed algorithm can solve job-oriented multi-objective FJSP efficiently and effectively.
| Original language | English |
|---|---|
| Pages (from-to) | 477-481 |
| Number of pages | 5 |
| Journal | Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University |
| Volume | 24 |
| Issue number | 4 |
| State | Published - Aug 2006 |
Keywords
- Integrated genetic algorithm
- Job-oriented multi-objective FJSP (Flexible Job Shop Scheduling Problem)
Fingerprint
Dive into the research topics of 'Proposing an integrated genetic algorithm for solving job-oriented multi-objective FJSP'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver