Abstract
Modeling real world problems precisely is a very difficult task as most of the objective and constraints can't be precisely defined and the data is either unavailable or indeterminate. Fortunately, this type of problem can be solved efficiently via fuzzy mathematical programming. This paper illustrates how a fuzzy linear programming approach be used to model and solve cell formation (CF) problems. We also examined different membership functions to see their impacts on the computational performance. This study reveals that Representing the CF problem using fuzzy set theory not only is a clever and flexible choice, it also can lead to improve the overall performance.
| Original language | English (US) |
|---|---|
| Title of host publication | IEEE International Conference on Fuzzy Systems |
| Publisher | IEEE |
| Pages | 1406-1411 |
| Number of pages | 6 |
| Volume | 2 |
| State | Published - 1994 |
| Event | Proceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3) - Orlando, FL, USA Duration: Jun 26 1994 → Jun 29 1994 |
Other
| Other | Proceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3) |
|---|---|
| City | Orlando, FL, USA |
| Period | 6/26/94 → 6/29/94 |
All Science Journal Classification (ASJC) codes
- Chemical Health and Safety
- Software
- Safety, Risk, Reliability and Quality