Qualitative behavior of stiff ODEs through a stochastic approach

Hande Uslu, Murat Sari*, Tahir Cosgun

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


In the last few decades, stiff differential equations have attracted a great deal of interest from academic society, because much of the real life is covered by stiff behavior. In addition to importance of producing model equations, capturing an exact behavior of the problem by dealing with a solution method is also handling issue. Although there are many explicit and implicit numerical methods for solving them, those methods cannot be properly applied due to their computational time, computational error or effort spent for construction of a structure. Therefore, simulation techniques can be taken into account in capturing the stiff behavior. In this respect, this study aims at analyzing stiff processes through stochastic approaches. Thus, a Monte Carlo based algorithm has been presented for solving some stiff ordinary differential equations and system of stiff linear ordinary differential equations. The produced results have been qualitatively and quantitatively discussed.

Original languageEnglish
Pages (from-to)181-187
Number of pages7
JournalInternational Journal of Optimization and Control: Theories and Applications
Issue number2
Publication statusPublished - 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2020 Balikesir University. All rights reserved.


The authors would like to thank the anonymous reviewers for their valuable comments and suggestions for improving the paper. The first author also would like to thank Scientific and Technological Research Council of Turkey (TUBITAK), under the 2211-E Program which supports the author.

FundersFunder number
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu


    • Monte Carlo method
    • Stiff differential equation
    • Stochastic approach


    Dive into the research topics of 'Qualitative behavior of stiff ODEs through a stochastic approach'. Together they form a unique fingerprint.

    Cite this