Computational Management Science

Aims & Scope

Computational Management Scienceis an international journal focusing on all computational aspects of management science.

These include theoretical and empirical analysis of computational models; computational statistics; analysis and applications of constrained, unconstrained, robust, stochastic and combinatorial optimisation algorithms; dynamic models, such as dynamic programming and decision trees; new search tools and algorithms for global optimisation, modelling, learning and forecasting; models and tools of knowledge acquisition.

The emphasis on computational paradigms is an intended feature of CMS, distinguishing it from more classical operations research journals.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	1.3
2024	1.30

Journal Rank

Year	Value
2024	11916

Journal Citation Indicator

Year	Value
2024	195

SJR (SCImago Journal Rank)

Year	Value
2024	0.483

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	42

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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
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Business, Management and Accounting, Computer Science and Decision Sciences, 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.

• ETSAP-TIAM: the TIMES integrated assessment model Part I: Model structure

  Citation: 368

  Authors: Richard, Maryse

• Quasi-variational inequalities, generalized Nash equilibria, and multi-leader-follower games

  Citation: 361

  Authors: Jong-Shi, Masao

• Progressive hedging innovations for a class of stochastic mixed-integer resource allocation problems

  Citation: 241

  Authors: Jean-Paul, David L.

• Supply chain network operations management of a blood banking system with cost and risk minimization

  Citation: 157

  Authors: Anna, Amir H., Min

• Scenario tree reduction for multistage stochastic programs

  Citation: 141

  Authors: Holger, Werner

• Likelihood robust optimization for data-driven problems

  Citation: 136

  Authors: Zizhuo, Peter W., Yinyu

• ETSAP-TIAM: the TIMES integrated assessment model. part II: mathematical formulation

  Citation: 135

  Authors: Richard

• Partitioning procedures for solving mixed-variables programming problems

  Citation: 115

  Authors: J. F.

• Global optimization of mixed-integer bilevel programming problems

  Citation: 104

  Authors: Zeynep H., Christodoulos A.

• Assessing interbank contagion using simulated networks

  Citation: 102

  Authors: Grzegorz, Christoffer

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