International Journal of Mathematical Modelling and Numerical Optimisation

Aims & Scope

The objectives of IJMMNO are to establish an excellent platform for discussion and communication between applied mathematicians, mathematical and numerical modellers, computer algorithm developers, and optimisation researchers in academic and research institutions, and industry.

It strives to promote the development of effective algorithms, mathematical models, and optimisation techniques and their applications in real-world problems with demonstrated capability and efficiency in cross-disciplinary and industrial applications.

View Aims & Scope

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Metrics & Ranking

Journal Rank

Year	Value
2024	24940

Journal Citation Indicator

Year	Value
2024	41

SJR (SCImago Journal Rank)

Year	Value
2024	0.145

Quartile

Year	Value
2024	Q4

h-index

Year	Value
2024	16

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Mathematics, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Engineering optimisation by cuckoo search

  Citation: 1089

  Authors: Xin She, Suash

• A literature survey of benchmark functions for global optimisation problems

  Citation: 577

  Authors: Momin, Xin She

• Efficient simulation and integrated likelihood estimation in state space models

  Citation: 187

  Authors: Joshua C.C., Ivan

• Predicting the present with Bayesian structural time series

  Citation: 167

  Authors: Steven L., Hal R.

• A comprehensive review of cuckoo search: variants and hybrids

  Citation: 44

  Authors: Iztok Fister, Dušan, Iztok

• Modelling and predicting the Bitcoin volatility using GARCH models

  Citation: 43

  Authors: Viviane Y., Marianne R.

• Application of derivative-free methodologies to generally constrained oil production optimisation problems

  Citation: 31

  Authors: David Echeverria, Obiajulu J., Louis J.

• A novel particle swarm optimisation with search space tuning parameter to avoid premature convergence

  Citation: 13

  Authors: Raja, R. Agilesh, D. Ashok, N.

• Hierarchical multiobjective approach for optimising RFID reader deployment

  Citation: 13

  Authors: Abdelkader, Badr Abou El

• Stochastic response surfaces based on non-intrusive polynomial chaos for uncertainty quantification

  Citation: 12

  Authors: Serhat

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