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Multi-level multi-objective decision problem through fuzzy random regression based objective function

机译:基于目标函数的模糊随机回归的多层次多目标决策问题

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A multi-level decision making problem confronts several issues especially in coordinating decision in hierarchic processes and in compromising conflicting objectives for each decision level. Therefore, its mathematical model plays a pivotal role in solving such problem, and is influencing to the final result. However, it is sometimes difficult to estimate the coefficients of objective functions of the model in real situations specifically when the statistical data contain random and fuzzy information. Thus, decision making scheme should provide an appropriate method to handle the presence of such uncertainties. Hence, this paper proposes a fuzzy random regression method to estimate the coefficients value for the objective functions of multi-level multi-objective model. The algorithm is constructed to obtain a satisfaction solution, which fulfills at least weak Pareto optimality. A numerical example illustrates the proposed solution procedure.
机译:多级决策问题面临多个问题,尤其是在分层流程中协调决策以及在每个决策级别折衷目标时。因此,其数学模型在解决此类问题中起着举足轻重的作用,并影响到最终结果。但是,有时在实际情况下,尤其是当统计数据包含随机和模糊信息时,很难估计模型的目标函数的系数。因此,决策方案应提供适当的方法来处理此类不确定性的存在。因此,本文提出了一种模糊随机回归方法来估计多级多目标模型目标函数的系数值。构造该算法以获得至少满足弱的帕累托最优性的满意解。数值示例说明了建议的求解过程。

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