Methodology and Computing in Applied Probability publishes high quality research and review articles in areas of applied probability that emphasize methodology and computing. The journal focuses on articles that examine important applications and that include detailed case studies.

With its policy of attracting papers representing a broad range of interests, the journal covers such topics as algorithms, approximations, combinatorial and geometric probability, communication networks, extreme value theory, finance, image analysis, inequalities, information theory, mathematical physics, molecular biology, Monte Carlo methods, order statistics, queuing theory, reliability theory, and stochastic processes.

  • Publishes high quality research and review articles in areas of applied probability that emphasize methodology and computing
  • Focuses on articles that examine important applications and that include detailed case studies
  • Attracts papers representing a broad range of interests
  • 100% of authors who answered a survey reported that they would definitely publish or probably publish in the journal again

Journal information

Editor-in-Chief
  • Joseph Glaz
Publishing model
Hybrid. Open Access options available

Journal metrics

0.746 (2018)
Impact factor
0.855 (2018)
Five year impact factor
104 days
Submission to first decision
381 days
Submission to acceptance
18,157 (2019)
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Latest articles

This journal has 39 open access articles

Journal updates

  • COVID-19 and impact on peer review

    As a result of the significant disruption that is being caused by the COVID-19 pandemic we are very aware that many researchers will have difficulty in meeting the timelines associated with our peer review process during normal times.  Please do let us know if you need additional time. Our systems will continue to remind you of the original timelines but we intend to be highly flexible at this time.

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About this journal

Electronic ISSN
1573-7713
Print ISSN
1387-5841
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