الفهرس 
AbstractOnly 14 pages are availabe for public view
 |  | from | 114 |  |  |
| | | from | 114 | | |
Abstract
In this thesis, we present a systematic and focused study of the application of Rough Sets to a basic area of decision theory, namely Mathematical Programming. This hybridization concerns the mathematical programming in rough environment and called “Rough Programming”. It implies the existence of the roughness in any part of the problem as a result of the leakage, uncertainty, and vagueness in the available information. We classified the rough programming problems into three classes according to the place of the roughness in the problem. In rough programming, wherever roughness exists, new concepts like “rough feasibility” and “rough optimality” come in the front of our interest and discussions. The study of convexity for rough programming problems plays a key role in understanding the global optimality in rough environment. For this, a theoretical framework of convexity in rough programming and conceptualization of the solution is created on the lines of their crisp counterparts.