A Case Study on Solutions of Linear Fractional Programming Problems
Rashmi Ranjan Ota, Swetarani Tripathy, Mitali Madhusmita Nayak
Abstract
Open-access reader
Rashmi Ranjan Ota, Swetarani Tripathy, Mitali Madhusmita Nayak
Abstract
Open-access reader
In some decision making problems, objective function can be defined as the ratio of two linear functional subjects to given constraints. These types of problems are known as linear fractional programming problems. The importance of linear fractional programming problems comes from the fact that many real life problems can be expressed as the ratio of physical or economical values represented by linear functions, for example traffic planning, game theory and production planning etc. In this article, correspond to a production planning problem the mathematical model developed, is a linear fractional programming and in order to solve it, various fractional programming techniques has been used. Finally result is compared with the solution obtained by graphical method. To illustrate the efficiency of stated method a numerical example has given.
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In some decision making problems, objective function can be defined as the ratio of two linear functional subjects to given constraints. These types of problems are known as linear fractional programming problems. The importance of linear fractional programming problems comes from the fact that many real life problems can be expressed as the ratio of physical or economical values represented by linear functions, for example traffic planning, game theory and production planning etc. In this article, correspond to a production planning problem the mathematical model developed, is a linear fractional programming and in order to solve it, various fractional programming techniques has been used. Finally result is compared with the solution obtained by graphical method. To illustrate the efficiency of stated method a numerical example has given.
Key concepts: Fractional programming, Linear-fractional programming, Linear programming, Mathematical optimization, Production planning, Production (economics), Computer science, Mathematics