Abstract
In this paper, an integrated machine tool selection and sequencing model is proposed. The model determines machine visiting sequences for all part types, such that the total production time for the production order is minimized and workloads among machine tools are balanced. The model is formulated as a 0-1 integer programming. To solve the model, a genetic algorithm approach based on a topological sort technique is developed. To demonstrate the efficiency of the proposed GA approach on the integrated machine tool selection and sequencing problem, a number of numerical experiments using various size problems are carried out. The numerical experiments show that the proposed GA approach is efficient to this problems.
| Original language | English |
|---|---|
| Pages (from-to) | 605-621 |
| Number of pages | 17 |
| Journal | Computers and Industrial Engineering |
| Volume | 43 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2002 Sep |
| Externally published | Yes |
Keywords
- Genetic algorithm
- Integrated machine selection
- Operation sequencing
ASJC Scopus subject areas
- Computer Science(all)
- Engineering(all)
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Cite this
Moon, C., Lee, M., Seo, Y., & Lee, Y. H. (2002). Integrated machine tool selection and operation sequencing with capacity and precedence constraints using genetic algorithm. Computers and Industrial Engineering, 43(3), 605-621. https://doi.org/10.1016/S0360-8352(02)00129-8