Solving Geometric Programming Problems with Normal, Linear and Zigzag Uncertainty Distributions
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DOI: 10.1007/s10957-016-0985-z
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Cited by:
- Belleh Fontem, 2023. "Robust Chance-Constrained Geometric Programming with Application to Demand Risk Mitigation," Journal of Optimization Theory and Applications, Springer, vol. 197(2), pages 765-797, May.
- Huang, Xiaoxia & Ma, Di & Choe, Kwang-Il, 2023. "Uncertain mean–variance portfolio model with inflation taking linear uncertainty distributions," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 203-217.
- Tingting Yang & Xiaoxia Huang, 2022. "A New Portfolio Optimization Model Under Tracking-Error Constraint with Linear Uncertainty Distributions," Journal of Optimization Theory and Applications, Springer, vol. 195(2), pages 723-747, November.
- Wasim Akram Mandal, 2021. "Weighted Tchebycheff Optimization Technique Under Uncertainty," Annals of Data Science, Springer, vol. 8(4), pages 709-731, December.
- Rashed Khanjani-Shiraz & Salman Khodayifar & Panos M. Pardalos, 2021. "Copula theory approach to stochastic geometric programming," Journal of Global Optimization, Springer, vol. 81(2), pages 435-468, October.
- Wasim Akram Mandal & Sahidul Islam, 2017. "Multiobjective geometric programming problem under uncertainty," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 27(4), pages 85-109.
- Dennis L. Bricker & K. O. Kortanek, 2017. "Perfect Duality in Solving Geometric Programming Problems Under Uncertainty," Journal of Optimization Theory and Applications, Springer, vol. 173(3), pages 1055-1065, June.
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Keywords
Uncertainty theory; Uncertain variable; Linear uncertainty distribution; Normal uncertainty distribution; Zigzag uncertainty distribution;All these keywords.
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