Solving Fractional Geometric Programming Problems via Relaxation approach

  • Mansour Saraj Shahid Chamran University of Ahvaz
Keywords: Fractional programming, Geometric Programming, Linearization technique


In the optimization literature , Geometric Programming problems play a very important role rather than primary in engineering designs. The geometric programming problem is a nonconvex optimization problem that has received the attention of many researchers in the recent decades. Our main focus in this issue is to solve a Fractional Geometric Programming(FGP) problem via linearization technique[1]. Linearizing separately both the numerator and denominator of the fractional geometric programming problem in the objective function, causes the problem to be reduced to a Fractional Linear Programming problem (FLPP) and then the transformed linearized FGP is solved by Charnes and Cooper method which in fact gives a lower bound solution to the problem. To illustrate the accuracy of the final solution in this approach, we will compar our result with the LINGO software solution of the initial FGP problem and we shall see a close solution to the globally optimum. A numerical example is given in the end to illustrate the methodology and efficiency of the proposed approach.


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How to Cite
Saraj, M. (2018). Solving Fractional Geometric Programming Problems via Relaxation approach. MathLAB Journal, 1(3), 370-383. Retrieved from
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