Amuji, H.O., Ugwuowo, F.I., Chukwu, W.I.E and Uche, P.I. (In press) A Modified Generalized Inverse Method for Solving Geometric Programming Problems with Extended Degrees of Difficulties. International Journal of Operational Research.
http://www.inderscience.com/info/ingeneral/forthcoming.php?jcode=ijor

has been cited by the following article:

• TITLE: Sensitivity Analysis on the Negative Degree of Difficulty Geometric Programming Problem

  AUTHORS: H. O. Amuji, N. P. Olewuezi, D. E. Onwuegbuchunam, C. Igboanusi

  KEYWORDS: Negative Degree of Difficulty, Sensitivity Analysis, Primal Decision Variables, Dual Decision Variables, Global Optimal Solution

  JOURNAL NAME: American Journal of Operations Research, Vol.10 No.1, January 17, 2020

  ABSTRACT: The range of optimal values in cost optimization models provides management with options for decision making. However, it can be quite challenging to achieve feasible range of optimality in Geometric programming (Gp) models having negative degrees of difficulty. In this paper, we conduct sensitivity analysis on the optimal solution of Geometric programming problem with negative degree of difficulty. Using imprest data, we determine the optimal objective function, dual decision variables, primal decision variables; the range of values, the cost coefficient and RHS constraint must lie for the solution to stay optimal. From the analysis, we established that incremental sensitivity analysis has the functional form .