Many results in mathematical programming involving convex functions hold for a more general class of functions, called invex functions. Examples of such functions are given. It is shown that several types of generalized convex functions are special cases of invex functions. The relationship between convexity and some generalizations of invexity is illustrated. A nonlinear problem with equality constraints is studied and necessary and sufficient conditions for optimality are stated in terms of invexity. Also, weak, strong and converse dual theorems for fractional programming are given using invexity conditions. Finally, a sufficient condition for invexity is established through the use of linear programming. / Source: Dissertation Abstracts International, Volume: 48-07, Section: B, page: 2087. / Thesis (Ph.D.)--The Florida State University, 1987.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_76148 |
| Contributors | RUEDA, NORMA GRACIELA., Florida State University |
| Source Sets | Florida State University |
| Detected Language | English |
| Type | Text |
| Format | 75 p. |
| Rights | On campus use only. |
| Relation | Dissertation Abstracts International |
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