2013Unpublished venueRequires access

TECHNOLOGY Convexity in Linear Fractional Programming Problem

Anita Biswas, Smita Verma

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Abstract

Linear programming is a mathematical programming technique to optimize performance under a set of resource constraints as specified by organization. Linear fractional programming is a generalization o f linear programming. The objective functions in linear prog rams are linear functions while the objective funct ion in a linear fractional program is a ratio of two linear functio ns. In his paper an attempt is made to solve the co nvexity in linear fractional programming problem by taking CCR model, which states that the collection of all feasible s olution to CCR model constitutes a convex set whose extreme points correspond to the basic feasible solutions.

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Linear programming is a mathematical programming technique to optimize performance under a set of resource constraints as specified by organization. Linear fractional programming is a generalization o f linear programming. The objective functions in linear prog rams are linear functions while the objective funct ion in a linear fractional program is a ratio of two linear functio ns. In his paper an attempt is made to solve the co nvexity in linear fractional programming problem by taking CCR model, which states that the collection of all feasible s olution to CCR model constitutes a convex set whose extreme points correspond to the basic feasible solutions.

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Available abstract

Linear programming is a mathematical programming technique to optimize performance under a set of resource constraints as specified by organization. Linear fractional programming is a generalization o f linear programming. The objective functions in linear prog rams are linear functions while the objective funct ion in a linear fractional program is a ratio of two linear functio ns. In his paper an attempt is made to solve the co nvexity in linear fractional programming problem by taking CCR model, which states that the collection of all feasible s olution to CCR model constitutes a convex set whose extreme points correspond to the basic feasible solutions.

Key concepts: Linear-fractional programming, Linear programming, Fractional programming, Convexity, Generalization, Mathematics, Criss-cross algorithm, Mathematical optimization

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