Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Numerical Techniques for Stochastic Optimization
1988434 citationsY. Ermoliev et al.IIASA PURE (International Institute of Applied Systems Analysis)profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Y. Ermoliev's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Y. Ermoliev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Y. Ermoliev more than expected).
This network shows the impact of papers produced by Y. Ermoliev. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Y. Ermoliev. The network helps show where Y. Ermoliev may publish in the future.
Co-authorship network of co-authors of Y. Ermoliev
This figure shows the co-authorship network connecting the top 25 collaborators of Y. Ermoliev.
A scholar is included among the top collaborators of Y. Ermoliev based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Y. Ermoliev. Y. Ermoliev is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zagorodny, А. G., et al.. (2014). Integrated Management, Security and Robustness. IIASA PURE (International Institute of Applied Systems Analysis).3 indexed citations
4.
Cano, Emilio L., Javier M. Moguerza, Afzal S. Siddiqui, T. Ermolieva, & Y. Ermoliev. (2012). Strategic model for energy systems optimisation: Aspects of energy efficiency and risk management. IIASA PURE (International Institute of Applied Systems Analysis).1 indexed citations
5.
Ermolieva, T., Y. Ermoliev, M. Jonas, Gad Fischer, & M. Makowski. (2010). A model for robust emission trading under uncertainties. IIASA PURE (International Institute of Applied Systems Analysis).1 indexed citations
6.
Ermolieva, T., et al.. (2010). Integrated modeling approach to the analysis of food security and sustainable rural developments: Ukrainian case study. IIASA PURE (International Institute of Applied Systems Analysis).2 indexed citations
7.
Ermolieva, T., et al.. (2007). The difference between deterministic and probabilistic detection of emission changes: Toward the use of the probabilistic verification time concept. IIASA PURE (International Institute of Applied Systems Analysis).1 indexed citations
8.
Amendola, A., Y. Ermoliev, & T. Ermolieva. (2000). Earthquake risk management: A case study for an Italian region. IIASA PURE (International Institute of Applied Systems Analysis).16 indexed citations
9.
Ermoliev, Y., T. Ermolieva, Gordon J. F. MacDonald, & V. I. Norkin. (1999). Optimization of catastrophic risk portfolios. IIASA PURE (International Institute of Applied Systems Analysis).3 indexed citations
10.
Ermoliev, Y., et al.. (1999). An energy model incorporating technological uncertainty, increasing returns and economic and environmental risks. IIASA PURE (International Institute of Applied Systems Analysis).2 indexed citations
11.
Ermolieva, T., Y. Ermoliev, & V. I. Norkin. (1997). On the role of advanced modeling in managing catastrophic risks. IIASA PURE (International Institute of Applied Systems Analysis).3 indexed citations
12.
Ermoliev, Y.. (1990). Adaptive Algorithms in Stochastic Optimization and Game Theory. IIASA PURE (International Institute of Applied Systems Analysis).12 indexed citations
13.
Ermoliev, Y. & Roger J.‐B. Wets. (1988). Stochastic programming, an introduction. Numerical techniques for stochastic optimization. IIASA PURE (International Institute of Applied Systems Analysis).32 indexed citations
14.
Ermoliev, Y., et al.. (1982). Mathematical Methods of Operation Research. IIASA PURE (International Institute of Applied Systems Analysis).9 indexed citations
Ermoliev, Y. & E. A. Nurminskii. (1980). Stochastic quasigradient algorithms for minimax problems in stochastic programming. IIASA PURE (International Institute of Applied Systems Analysis).1 indexed citations
17.
Ermoliev, Y. & Y.M. Kaniovski. (1979). Asymptotic properties of some stochastic programming methods with constant step. IIASA PURE (International Institute of Applied Systems Analysis).1 indexed citations
18.
Ermoliev, Y., et al.. (1979). Stochastic Models in Economics. IIASA PURE (International Institute of Applied Systems Analysis).3 indexed citations
19.
Ermoliev, Y.. (1976). Stochastic Programming Methods. IIASA PURE (International Institute of Applied Systems Analysis).91 indexed citations
20.
Ermoliev, Y.. (1973). Selected translations in mathematical statistics and probability. IIASA PURE (International Institute of Applied Systems Analysis).3 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.