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A New Optimization Model about Enterprise Equipment Investment Project based on Integrated Entropy Weight and Fuzzy Matter Element
並列摘要
The equipment investment scheme evaluation of enterprise is usually multi-objective optimization problem affected by many factors. Among many optimization methods, the common fuzzy matter element is based on the matter-element analysis and combined with the concepts of fuzzy mathematics, which can reflect the subjective fuzzy judgment; the common entropy weight method makes use of the judgment matrix composed of evaluation index value, Weights gotten by the common entropy weight method mainly reflects usefulness of data and can't reflect actual importance of evaluation indexes. Considering this fact, this study integrates engineering economics, reliability theory, fuzzy matter element and entropy theory presents a new optimization model about enterprise equipment investment project and also presents detailed methods and steps of application of integrated model in concrete example, which can offer the reference for project investment activity of practical enterprise equipment.
延伸閱讀
- Wang, L. (2020). A Multi-criteria Group Decision Making Method and Its Applications Based on Improved Intuitionistic Fuzzy Entropy and Information Integration Operator. International Journal of Information and Management Sciences, 31(4), 375-392. https://doi.org/10.6186/IJIMS.202012_31(4).0004
- Hu, T. W. (2008). The Study and Applications of Combining Interval Type-2 Fuzzy Asymmetric Membership Functions and Recurrent Neural Network System [master's thesis, Yuan Ze University]. Airiti Library. https://doi.org/10.6838/YZU.2008.00286
- Zeng, T., & Jiang, Z. (2022). Empirical Analysis of EOQ Procurement Model Based on AHP-entropy Weight Classification Management. International Journal of Social Science and Education Research, 5(7), 565-574. https://doi.org/10.6918/IJOSSER.202207_5(7).0086
- Tsai, H. R., & Chen, T. (2013). A Fuzzy Nonlinear Programming Approach for Optimizing the Performance of a Four-Objective Fluctuation Smoothing Rule in a Wafer Fabrication Factory. Journal of Applied Mathematics, 2013(), 284-298-628. https://doi.org/10.1155/2013/720607
- Azimi, M., & Rasekh, A. (2010). Generalized Maximum Entropy Estimation in Measurement Error Models. International Journal of Intelligent Technologies and Applied Statistics, 3(4), 363-382. https://doi.org/10.6148/IJITAS.2010.0304.01