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08 de abril - 10 de abril de 2026

Clasificación: B (CORE2023)Offline

European Conference on Evolutionary Computation in Combinatorial Optimisation

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Toulouse, FranceSpringer Nature

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Resumen General

The 26th European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP) is a multidisciplinary conference focusing on applications and theory of evolutionary computation methods and other metaheuristics for solving difficult combinatorial optimisation problems. EvoCOP 2026 will be held in Toulouse, France from 8-10 April 2026, as part of EvoStar.

Convocatoria

EvoCOP 2026: Call for Papers

The 26th European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP) will be held in Toulouse, France, from April 8-10, 2026, as part of the EvoStar event.

EvoCOP brings together researchers working on applications and theory of evolutionary computation methods and other metaheuristics for solving difficult combinatorial optimisation problems.

Areas of Interest and Contributions

EvoCOP welcomes submissions in all experimental and theoretical aspects of evolutionary computation and other metaheuristics to combinatorial optimisation problems, including (but not limited to) the following areas:

  • Applications of metaheuristics to combinatorial optimization problems
  • Theoretical developments
  • Neighbourhoods and efficient algorithms for searching them
  • Variation operators for stochastic search methods
  • Constraint-handling techniques
  • Parallelisation and grid computing
  • Search space and landscape analyses
  • Comparisons between different (also exact) methods
  • Automatic algorithm configuration and design

Prominent examples of metaheuristics include (but are not limited to):

  • Evolutionary algorithms
  • Estimation of distribution algorithms
  • Swarm intelligence methods such as ant colony and particle swarm optimisation
  • Artificial immune systems
  • Local search methods such as simulated annealing, tabu search, variable neighbourhood search, iterated local search, scatter search and path relinking
  • Hybrid methods such as memetic algorithms
  • Matheuristics (hybrids of exact and heuristic methods)
  • Hyper-heuristics and autonomous search
  • Surrogate-model-based methods

Note that continuous/numerical optimisation is not part of the topics of interest of EvoCOP.

Submission Details

Accepted papers will be published by Springer Nature in the Lecture Notes in Computer Science series.

Submissions must be original and not published elsewhere. They will be peer reviewed by at least three members of the program committee. The reviewing process will be double-blind, so please omit information about the authors in the submitted paper. Submit your manuscript in Springer LNCS format.

  • Page limit: 14 + unlimited references pages
  • Submission Deadline: November 1, 2025 AoE

Important Dates

EventDate
EvoApps Special Session Proposals8 September 2025
Submission deadline1 November 2025
Notification to authors10 January 2026
Camera-ready submission24 January 2026
Author's mandatory registration11 February 2026
Early registration deadline4 March 2026
Late-Breaking Abstracts submission29 March 2026
EvoStar Conference8-10 April 2026

Conference Chairs

  • Martin Krejca
    Ecole Polytechnique, France
    martin.krejca(at)polytechnique.edu
  • Nelishia Pillay
    University of Pretoria, South Africa
    nelishia.pillay(at)up.ac.za

For further information please visit https://www.evostar.org/2026/evocop

Fechas Importantes

Fechas del Congreso

Conference Date

8 de abril de 202610 de abril de 2026

Envío

(EvoApps Special Session) Proposals

8 de septiembre de 2025

Submission deadline

1 de noviembre de 2025

Late-Breaking Abstracts submission

29 de marzo de 2026

Notificación

Notification to authors

10 de enero de 2026

Versión Final

Camera-ready submission

24 de enero de 2026

Inscripción

Author's mandatory registration

11 de febrero de 2026

Early registration deadline

4 de marzo de 2026

Clasificación de la Fuente

Fuente: CORE2023

Clasificación: B

Campo de Investigación: Artificial intelligence

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