الفهرس 
A Survey on Related TopicsOnly 14 pages are availabe for public view
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Abstract
Mathematical programming plays an important role in facilitating managerial decision situations in a large number of domains. An important class of mathematical programming problems is linear fractional programming problems which deals with situations where a ratio of physical and/or economical linear functions is to be maximized/minimized. Linear fractional programming is a useful tool in production planning, financial and corporate planning, health care and hospital planning etc. Therefore, it is better to fit the real world problems within the framework of linear fractional programming. In conventional linear fractional programming models, all the data is assumed to be well defined and precise. However, in real world environment, it is not a realistic assumption. Usually, the value of many parameters is estimated by experts and it can’t be assumed the knowledge of the experts is always so precise. In this thesis, the modeling of input data inaccuracy will be made by the concepts of rough intervals or fuzzy rough numbers to deal with these situations.
The general purpose of this study is to investigate how to solve integer linear fractional programming problems with uncertainty coefficients.