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  • 标题:An Alternative Approach to the Solution of Multi-Objective Geometric Programming Problems
  • 本地全文:下载
  • 作者:Ersoy Öz ; Nuran Güzel ; Selçuk Alp
  • 期刊名称:Open Journal of Optimization
  • 印刷版ISSN:2325-7105
  • 电子版ISSN:2325-7091
  • 出版年度:2017
  • 卷号:06
  • 期号:01
  • 页码:11-25
  • DOI:10.4236/ojop.2017.61002
  • 语种:English
  • 出版社:Scientific Research Publishing
  • 摘要: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.
  • 关键词:Multi Objective Geometric Programming;Kuhn-Tucker Conditions;Taylor Series Expansion;Numerical Method;Weighted Mean Method
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