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Inverse optimization for linear fractional programming problem with bounded decision variables | ||
| Journal of New Researches in Mathematics | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 11 بهمن 1401 | ||
| نوع مقاله: research paper | ||
| شناسه دیجیتال (DOI): 10.30495/jnrm.2023.69593.2332 | ||
| نویسنده | ||
Ali Hamzehee  
| ||
| گروه ریاضی، دانشگاه آزاد اسلامی واحد کرمان، کرمان، ایران | ||
| چکیده | ||
| Inverse optimization is a modern study in operation research topics that is taken into consideration of researchers in recent three decades. In fact, the purpose of inverse optimization is adjustment in the parameter values of a mathematical programming problem until a given feasible point of those problem arrives to optimality. If this is possible, then those parameter values be must found that require minimum adjustments. In this paper, a branch of the inverse optimization for linear fractional programming problem with bounded decision variables is investigated that have wide applications in industrial area in order to optimize production. To this end, the duality relations and complementary slackness conditions of linear programming problems are used. Next, the conditions for a feasible solution, in order to be optimized by adjusting parameter values of the objective function, are stated and discussed. Finally, a numerical example of the proposed method with complete analysis is presented. | ||
| کلیدواژه‌ها | ||
| Inverse optimization؛ Linear fractional programming؛ Complementary slackness conditions؛ Bounded variables | ||
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آمار تعداد مشاهده مقاله: 31 |
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