Stochastic Optimization Models for Risk-Based Reservoir Management*

Autor: Tatiana Ermolieva, Pavel S. Knopov, Michael Obersteiner, V.M. Gorbachuk, Yu. M. Ermoliev, Taher Kahil

Publikováno v: Cybernetics and Systems Analysis. 55:55-64

The paper provides an overview of publications on reservoir management and formulates a novel stochastic dynamic optimization model for water balance management in the area affected. The proposed stochastic optimization approach allows multiple key p

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::84f063b975283369e0f426e23e642ba4
https://doi.org/10.1007/s10559-019-00112-z

Systems Analysis of Robust Strategic Decisions to Plan Secure Food, Energy, and Water Provision Based on the Stochastic Globiom Model

Autor: T. Yu. Ermolieva, Yu. M. Ermoliev, Nikolay Khabarov, Petr Havlik, Aline Mosnier, David Leclère, Michael Obersteiner, F. Kraksner

Publikováno v: Cybernetics and Systems Analysis. 51:125-133

The paper focuses on the development of adequate approaches to the systems analysis of geographically explicit robust decisions for long-term consistent management of interdependent land use systems. We introduce a stochastic partial equilibrium Glob

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::46566808edc5c86f0ca9ad0c3951d496
https://doi.org/10.1007/s10559-015-9704-2

Estimating reliability parameters under insufficient information

Autor: Yu. M. Ermoliev, Pavel S. Knopov, A. N. Golodnikov

Publikováno v: Cybernetics and Systems Analysis. 46:443-459

The paper presents an algorithm to search for the lower bound of the Bayesian estimate of the parameter of exponential distribution in the case where it is known that a priori distribution belongs to the class of all distribution functions with two e

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::eb28db49876827e7eefdb09f6b674440
https://doi.org/10.1007/s10559-010-9219-9

Solution of Nonconvex Nonsmooth Stochastic Optimization Problems

Autor: Vladimir I. Norkin, Yu. M. Ermoliev

Publikováno v: Cybernetics and Systems Analysis. 39:701-715

Different classes of nonconvex nonsmooth stochastic optimization problems are analyzed, their generalized differentiability properties and necessary optimality conditions are studied, and a technique for calculating stochastic gradients is developed.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7e783c267a48e57c389eb1a645278a52
https://doi.org/10.1023/b:casa.0000012091.84864.65

Global convergence of the stochastic tatonnement process

Autor: Vladimir I. Norkin, Michiel Keyzer, Yu. M. Ermoliev

Publikováno v: Journal of Mathematical Economics, 34, 173-190. Elsevier
Ermoliev, Y, Keyzer, M A & Norkin, V 2000, ' Global convergence of the stochastic tatonnement process ', Journal of Mathematical Economics, vol. 34, pp. 173-190 . https://doi.org/10.1016/S0304-4068(00)00037-9

The paper introduces stochastic elements into the Walrasian tâtonnement process, both to make it more realistic and to ensure its global convergence, with probability 1. It is assumed that the aggregate excess demand satisfies standard assumptions b

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b37712818b68d73c7cfe833f76bf2af
https://doi.org/10.1016/s0304-4068(00)00037-9