UDC 330.115
1 International Institute for Applied Systems Analysis, Laxenburg, Austria; V.M. Glushkov
Institute of Cybernetics of the NAS of Ukraine, Kyiv, Ukraine
ermoliev@iiasa.ac.at
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2 Bogolyubov Institute for Theoretical Physics of the NAS of Ukraine, Kyiv, Ukraine
Zagorodny@nas.gov.ua
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3 S.P. Timoshenko Institute of Mechanics of the NAS of Ukraine, Kyiv, Ukraine
Bogdanov@nas.gov.ua
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4 International Institute for Applied Systems Analysis, Laxenburg, Austria
ermol@iiasa.ac.at
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ROBUST FOOD–ENERGY–WATER–ENVIRONMENTAL SECURITY MANAGEMENT:
STOCHASTIC QUASIGRADIENT PROCEDURE
FOR LINKAGE OF DISTRIBUTED
OPTIMIZATION MODELS UNDER ASYMMETRIC INFORMATION AND UNCERTAINTY
Abstract. The paper presents a consistent algorithm for regional and sectoral distributed models’ linkage
and optimization under asymmetric information based on iterative stochastic quasigradient (SQG) solution procedure
of, in general, non-smooth nondifferentiable optimization. The procedure is used for linking individual sectoral
and regional models for integrated and interdependent food–energy–water–environmental security analysis and management.
Keywords: decision support, asymmetric information, linkage, SQG solution procedure, non-smooth optimization, subgradient, integrated modeling, food–energy–water–environmental nexus.
FULL TEXT
REFERENCES
- Ermoliev Y. Stochastic quasigradient methods in minimax problems. In: Encyclopedia of Optimization. Floudas C.A., Pardalos P.M. (Eds.). New York: Springer-Verlag, 2009. P. 3813–3818.
- Ermoliev Y. Two-stage stochastic programming: quasigradient method. In: Encyclopedia of Optimization. Floudas C.A., Pardalos P.M. (Eds.). New York: Springer-Verlag, 2009. P. 3955–3959.
- Ermoliev Y. Stochastic quasigradient methods: applications. In: Encyclopedia of Optimization. Floudas C.A., Pardalos P.M. (Eds.). New York: Springer-Verlag, 2009. P. 3807–3813.
- Ermoliev Y. Stochastic quasigradient methods. In: Encyclopedia of Optimization. Floudas C.A., Pardalos P.M. (Eds.). New York: Springer-Verlag, 2009. P. 3801–3807.
- Ermoliev Y., Norkin V. On nonsmooth and discontinuous problems of stochastic systems optimization. European Journal of Operational Research. 1997. Vol. 101, Iss. 2. P. 230–244. https://doi.org/10.1016/S0377-2217(96)00395-5.
- Ermolieva T., Ermoliev Y., Rovenskaya E., Obersteiner M. Two-stage nonsmooth stochastic optimization and iterative stochastic quasigradient procedures for robust estimation, machine learning and decision making. In: Resilience in the Digital Age. Roberts F.S., Sheremet I. (Eds.). Springer International Publishing, 2021. P. 45–74.
- Food-Energy-Water NEXUS for Sustainable Development: Integrated Modeling and Robust management. Zagorodny A.G., Ermoliev Yu.M., Bogdanov V.L., Ermolieva T. (Eds.). Kyiv: PH “Akademperiodyka”. 2020. 446 p. URL: https://ru.calameo.com/read/0031683726252f5034d74.
- Zagorodny A.G., Ermoliev Y., Bogdanov V.L., Kostyuchenko Y.V., Ermolieva. T. Integrated robust management of food-energy-water-land use nexus for sustainable development. In: Food-Energy-Water NEXUS for Sustainable Development: Integrated Modeling and Robust management. Zagorodny A.G., Ermoliev Yu.M., Bogdanov V.L., Ermolieva T. (Eds.). Kyiv: PH “Akademperiodyka”, 2020. P. 237–250.
- Ermoliev Y., Zagorodny A.G., Bogdanov V.L., Ermolieva T., Havlik P., Obersteiner M., Rovenskaya E. Linking distributed sectorial and regional optimization models under asymmetric information: towards robust food-water-energy-environmental nexus. In: Food-Energy-Water NEXUS for Sustainable Development: Integrated Modeling and Robust management. Zagorodny A.G., Ermoliev Yu.M., Bogdanov V.L., Ermolieva T. (Eds.). Kyiv: PH “Akademperiodyka”, 2020. P. 303–323.
- Ermoliev Y., Zagorodny A.G., Bogdanov V.L., Knopov P.S., Borodina O.M., Ermolieva T., Rovenskaya E., Kostjuchenk Y.V., et al. Integrated robust management of NEXUS between agricultural, water, energy economic sectors: consistent algorithms for linking distributed models. Proc. 6th International Conference on Mathematical Modeling, Optimization and Information Technologies (12–16 November, 2018, Kischinev, Moldova). Kischinev, 2018. P. 108–112.
- Gao J., Xu X., Cao G., Ermoliev Y.M., Ermolieva T.Y., Rovenskaya E.A. Optimizing regional food and energy. Sustainability. 2018. Vol. 10, Iss. 6. 1689. https://doi.org/10.3390/su10061689.
- Ermoliev Y. Production under limited water availability through integrated modeling. Some problems of linkage systems. IIASA Working Paper WP-80-102. Laxenburg, Austria: Int. Institute for Applied Systems Analysis (IIASA), 1980. 15 p. URL: http://pure.iiasa.ac.at/id/eprint/1367/1/WP-80-102.pdf.
- Arrow K.J. Studies in linear and nonlinear programming. Stanford, CA: Stanford University Press, 1958. 229 p.
- Bertsekas D. Nonlinear programming. Belmont: Atlanta Scientific, 1999. 791 p.
- Ermoliev Y. Methods of stochastic programming. Moscow: Nauka, 1976. 240 p. (In Russian).
- Rockafeller R.T. The theory of subgradient and its application to problems of optimization: convex and nonconvex functions. Berlin: Helderman Verlag, 1981. 107 p.
- Ermoliev Y., Robinson S., Rovenskaya E., Ermolieva T. Integrated catastrophic risk management: Robust balance between Ex-ante and Ex-post measures. SIAM News. 2018. Vol. 51, Iss. 6. P. 4.
- Ermoliev Y., Ermolieva T., MacDonald G., Norkin V. Stochastic optimization of insurance portfolios for managing exposure to catastrophic risks. Annals of Operations Research. 2000. Vol. 99, Iss. 1. P. 207–225.
- Ermolieva T., Ermoliev Y., Fischer G., Galambos I. The role of financial instruments in integrated catastrophic flood management. Multinational Finance Journal. 2003. Vol. 7, Iss. 3–4. P. 207–230.
- Ermoliev Y., von Winterfeldt D. Systemic risk and security management. In: Managing safety of heterogeneous systems: Decisions under uncertainty and risks. Ermoliev Y., Makowski M., Marti K. (Eds.). New York: Springer, 2012. P. 19–49. URL: link.springer.com/chapter/10.1007/ 978-3-642-22884-1_2.
- Ermolieva T., Ermoliev Y. Catastrophic risk management: flood and seismic risk case studies. In: Applications of Stochastic Programming. MOS-SIAM Series on Optimization. Wallace S.W., Ziemba W.T. (Eds.). 2005. P. 425–444.
- Ermoliev Y., Gaivoronski A. Stochastic quasigradient methods for optimization of discrete event systems. Annals of Operations Research. 1992. Vol. 39, Iss. 1. P. 1–39. URL: https://link.springer.com/article/10.1007%2FBF02060934.
- Gaivoronski A. Convergence properties of backpropagation for neural nets via theory of stochastic guasigradient methods. Part 1. Optimization Methods and Software. 1994. Vol. 4, Iss. 2. P. 117–134.
- Ermoliev Y., Michalevich M., Uteuliev N.U. Economic modeling of international water use (The case of the Aral Sea Basin). Cybernetics and Systems Analysis. 1994. Vol. 30, N 4. P. 523–527. https://doi.org/10.1007/BF02366562.
- Ermoliev Y., Wets R.J-B. Numerical techniques for stochastic optimization. Heidelberg: Springer-Verlag, 1988. XV, 571 p.
- Dantzig G.B., Wolfe P. The decomposition principle for linear programming. Econometrica. 1961. Vol. 29, N 4. P. 767–778.
- Kim K., Nazareth J.L. The decomposition principle and algorithms for linear programming. Linear Algebra and Its Applications. 1991. Vol. 152. P. 119–133.