نتایج جستجو برای: multiple objective fractional programming
تعداد نتایج: 1607300 فیلتر نتایج به سال:
The weighted sums approach for linear and convex multiple criteria optimization is well studied. The weights determine a linear function of the criteria approximating a decision makers overall utility. Any efficient solution may be found in this way. This is not the case for multiple criteria integer programming. However, in this case one may apply the more general e-constraint approach, result...
In this paper, two approaches were introduced to obtain Stackelberg solutions for two-level linear fractional programming problems with interval coefficients in the objective functions. The approaches were based on the Kth best method and the method for solving linear fractional programming problems with interval coefficients in the objective function. In the first approach, linear fractional p...
The sum of a fractional program is a nonconvex optimization problem in the field of fractional programming and it is difficult to solve. The development of research is restricted to single objective sums of fractional problems only. The branch and bound methods/algorithms are developed in the literature for this problem as a single objective problem. The theoretical and algorithmic development ...
Multiple Objective Programming (MOP) problems have become famous among many researchers due to more practical and realistic implementations. There have been a lot of methods proposed especially during the past four decades. In this paper, we develop a new algorithm based on a new approach to solve MOP problems by starting from a utopian point (which is usually infeasible) and moving towards the...
abstract it is the purpose of this article to introduce a linear approximation technique for solving a fractional chance constrained programming (cc) problem. for this purpose, a fuzzy goal programming model of the equivalent deterministic form of the fractional chance constrained programming is provided and then the process of defuzzification and linearization of the problem is started. a samp...
data envelopment analysis (dea) is a technique used to evaluate the relative efficiency of comparable decision making units (dmus) with multiple input-output. it computes a scalar measure of efficiency and discriminates between efficient and inefficient dmus. it can also provide reference units for inefficient dmus without consideration of the decision makers’ (dms) preferences. in this paper, ...
in this paper imprecise target models has been proposed to investigate the relation between imprecise data envelopment analysis (idea) and mini-max reference point formulations. through these models, the decision makers' preferences are involved in interactive trade-off analysis procedures in multiple objective linear programming with imprecise data. in addition, the gradient projection type me...
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