Ota, R.R. and Ojha, A.K. (2015) A Comparative Study on Optimization Techniques for Solving Multi-Objective Geometric Programming Problems. Applied Mathematical Sciences, 9, 1077-1085.
https://doi.org/10.12988/ams.2015.4121029

has been cited by the following article:

• TITLE: An Alternative Approach to the Solution of Multi-Objective Geometric Programming Problems

  AUTHORS: Ersoy Öz, Nuran Güzel, Selçuk Alp

  KEYWORDS: Multi Objective Geometric Programming, Kuhn-Tucker Conditions, Taylor Series Expansion, Numerical Method, Weighted Mean Method

  JOURNAL NAME: Open Journal of Optimization, Vol.6 No.1, March 7, 2017

  ABSTRACT: The aim of this study is to present an alternative approach for solving the multi-objective posynomial geometric programming problems. The proposed approach minimizes the weighted objective function comes from multi-objective geometric programming problem subject to constraints which constructed by using Kuhn-Tucker Conditions. A new nonlinear problem formed by this approach is solved iteratively. The solution of this approach gives the Pareto optimal solution for the multi-objective posynomial geometric programming problem. To demonstrate the performance of this approach, a problem which was solved with a weighted mean method by Ojha and Biswal (2010) is used. The comparison of solutions between two methods shows that similar results are obtained. In this manner, the proposed approach can be used as an alternative of weighted mean method.