Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
468898 | Computers & Mathematics with Applications | 2011 | 8 Pages |
Abstract
In this paper, we consider minimizing multiple linear objective functions under a max-tt-norm fuzzy relational equation constraint. Since the feasible domain of a max–Archimedean tt-norm relational equation constraint is generally nonconvex, traditional mathematical programming techniques may have difficulty in yielding efficient solutions for such problems. In this paper, we apply the two-phase approach, utilizing the min operator and the average operator to aggregate those objectives, to yield an efficient solution. A numerical example is provided to illustrate the procedure.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Sy-Ming Guu, Yan-Kuen Wu, E.S. Lee,