Supervisor:Dr Prabhjot Kaur
Authored By:
Pravahan Jaivili (IMH/10046/18)
Ketan Raj (IMH/10015/18)
Detailed Report : https://github.com/ketanraj15/The-Knox-Production-Mix-Selection-Problem/blob/80f5bd286ca9424db691bf2182588a8e0be2b5e7/Report.md
Tora Detailed Solution : https://github.com/ketanraj15/The-Knox-Production-Mix-Selection-Problem/blob/80f5bd286ca9424db691bf2182588a8e0be2b5e7/Simplex%20Solution.pdf
In problems of classical system analysis, it is ubiquitous to treat imprecision by the use of probability theory. It is becoming increasingly clear, however, that in the case of many real world problems involving large scale systems such as economic systems, social systems, mass service systems, etc., the major source of imprecision should more properly be labeled ‘fuzziness’ rather than ‘randomness.’ By fuzziness, we mean the type of imprecision which is associated with the lack of sharp transition from membership to nonmembership, as in tall men, small numbers, likely events, etc. In our approach, the emphasis is on mathematical programming and the use of the concept of a level set to extend some of the classical results to problems involving fuzzy constraints and objective functions.