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Fuzzy type-Ⅱ De-Novo programming for resource allocation and target setting in network data envelopment analysis: A natural gas supply chain

机译:网络数据包络分析中资源分配和目标设定的模糊Ⅱ型De-Novo规划:天然气供应链

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Developing effective approaches to design optimal resources of system based on the concepts of benchmark in DEA and optimal design in De-Novo programming is one of the important managerial decision making problems. In this paper, a decision support system is developed for allocation of resources and setting the targets across a set of entities in an equitable manner in presence of uncertainty. The proposed approach has two main modules. First, the most suitable system is designed using De-Novo programming. De-Novo programming. De-Novo programming is used to optimally determine the inputs (i.e., resources) and outputs (i.e., targets) of DMUs in network DEA rather than optimizing existing DMUs. Then, the optimal values of resources are allocated and optimal values of the targets are set in a complex network structure. Furthermore, in real-world problems budget of resources and targets are usually mixed with uncertainties, so in this paper, two concept of fuzzy and interval type-II fuzzy resources and target are developed for resource allocation and target setting. Finally numerical example based on real case of natural gas supply chain is also used to evaluate the applicability and efficacy of the proposed models. (C) 2018 Elsevier Ltd. All rights reserved.
机译:基于DEA的基准概念和De-Novo编程的优化设计,开发有效的方法来设计系统的最佳资源是重要的管理决策问题之一。在本文中,开发了一种决策支持系统,用于在存在不确定性的情况下以公平的方式分配资源并跨一组实体设置目标。提议的方法有两个主要模块。首先,使用De-Novo编程设计最合适的系统。 De-Novo编程。 De-Novo编程用于优化确定网络DEA中DMU的输入(即资源)和输出(即目标),而不是优化现有DMU。然后,在复杂的网络结构中分配资源的最佳值,并设置目标的最佳值。此外,在现实世界中,资源和目标的预算通常带有不确定性,因此,本文针对资源分配和目标设定提出了模糊和区间II型模糊资源和目标这两个概念。最后,基于天然气供应链实际案例的数值算例也被用来评估所提出模型的适用性和有效性。 (C)2018 Elsevier Ltd.保留所有权利。

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