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A fuzzy method to repair infeasibility in linearly constrained problems ~☆

机译:修正线性约束问题不可行的模糊方法〜☆

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摘要

In this paper we introduce a fuzzy method to deal with infeasibility in linearly constrained programs. Given an infeasible instance, we determine how much we should perturb the right-hand side coefficients in order to attain feasibility and propose a 'feasible reformulation' of the problem. Although we prove that our algorithm always finds such a reformulation the convenience of using it can be decided by the analyst. By this we mean that the method also provides a simple way to compute lower bounds on the changes on every right-hand side coefficient, and if the decision maker considers that some of the magnitudes are unacceptable, he or she simply stops at this step. We think that it will be specially useful for those situations in which the cause of the infeasibility is in the requirement of specifying exact values for the parameters in the mathematical programs formulation.
机译:在本文中,我们引入了一种模糊方法来处理线性约束程序中的不可行问题。给定一个不可行的实例,我们确定应该多少扰动右侧系数才能获得可行性,并提出该问题的“可行的重新表述”。尽管我们证明了我们的算法总能找到这样的重新定义形式,但是使用它的便利性可以由分析师确定。由此,我们的意思是该方法还提供了一种简单的方法来计算每个右侧系数变化的下限,并且如果决策者认为某些幅度是不可接受的,则他或她只需在此步骤停止即可。我们认为,对于那些不可行的原因是需要为数学程序公式中的参数指定精确值的情况,它将特别有用。

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