IEEE Transactions on Evolutionary Computation

Aims & Scope

IEEE Transactions on Evolutionary Computation publishes archival quality original papers in evolutionary computation and related areas including nature-inspired algorithms, population-based methods, and optimization where selection and variation are integral, and hybrid systems where these paradigms are combined.

Purely theoretical papers are considered as are application papers that provide general insights into these areas of computation.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	12

SJR (SCImago Journal Rank)

Year	Value
2024	3.495

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	222

Journal Rank

Year	Value
2024	541

Journal Citation Indicator

Year	Value
2024	5263

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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 Computer Science and 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.

• A fast and elitist multiobjective genetic algorithm: NSGA-II

  Citation: 37957

  Authors: K., A., S., T.

• No free lunch theorems for optimization

  Citation: 10735

  Authors: D.H., W.G.

• MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition

  Citation: 8005

  Authors:

• The particle swarm - explosion, stability, and convergence in a multidimensional complex space

  Citation: 7038

  Authors: M., J.

• Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach

  Citation: 6747

  Authors: E., L.

• Ant colony system: a cooperative learning approach to the traveling salesman problem

  Citation: 5793

  Authors: M., L.M.

• An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints

  Citation: 5448

  Authors: Kalyanmoy, Himanshu

• Differential Evolution: A Survey of the State-of-the-Art

  Citation: 4368

  Authors: Swagatam, Ponnuthurai Nagaratnam

• Handling multiple objectives with particle swarm optimization

  Citation: 3669

  Authors: C.A.C., G.T., M.S.

• Biogeography-Based Optimization

  Citation: 3554

  Authors: D.

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