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Choosing Robust Solutions In Discrete Optimization Problems Withfuzzy Costs

机译:在具有模糊成本的离散优化问题中选择鲁棒的解决方案

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摘要

In this paper a wide class of discrete optimization problems, which can be formulated as a 0-1 linear programming problem is discussed. It is assumed that the objective function costs are not precisely known. This uncertainty is modeled by specifying a finite set of fuzzy scenarios. Under every fuzzy scenario the costs are given as fuzzy intervals. Possibility theory is then applied to chose a solution in such a problem and mixed integer linear programming models are proposed to compute this solution.
机译:在本文中,讨论了各种各样的离散优化问题,这些问题可以表述为0-1线性规划问题。假定目标函数成本未知。通过指定有限的模糊场景来对这种不确定性进行建模。在每种模糊情况下,成本均以模糊间隔给出。然后应用可能性理论选择此类问题的解决方案,并提出了混合整数线性规划模型来计算该解决方案。

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