International Journal of Combinatorial Optimization Problems and Informatics

The International Journal of Combinatorial Optimization Problems and Informatics (IJCOPI) provides a forum for the dissemination and discussion of research in combinatorial optimisation and informatics. The journal publishes peer-reviewed contributions focused on the development of new problems, methods, techniques, and algorithms.

The journal supports both theoretical and applied research, promoting interdisciplinary approaches in areas such as optimisation, artificial intelligence, data science, and smart technologies.

IJCOPI is an open access journal that ensures free and unrestricted access to its content. All submissions undergo a rigorous peer-review process to guarantee their quality, validity, and relevance.

The journal follows a regular publication schedule, organizing issues throughout the year to ensure the timely dissemination of research results.

Machine-Readable Metadata and Scholarly Discovery

IJCOPI provides structured bibliographic metadata for its published articles to support scholarly discovery, citation linking, and machine-readable research infrastructure.

Published articles are assigned persistent Digital Object Identifiers (DOIs) and include structured metadata such as article title, authorship, institutional affiliations, abstract, keywords, publication date, volume, issue, pagination or article identifier, references, and licensing information.

IJCOPI supports open scholarly discovery through interoperable metadata standards and persistent identifiers. Article metadata and references are deposited with Crossref, and published content is openly accessible from the journal platform.

The journal encourages authors to provide ORCID identifiers and persistent identifiers for datasets, software, and other research outputs whenever available.

Abstract Requirements

Abstracts should clearly identify the research problem, objective, methodology, principal results, and main contribution of the study. Authors should use precise disciplinary terminology and explicitly identify the algorithms, models, datasets, experimental setting, or computational methods that are central to the research.

Abstracts should be self-contained and should avoid generic statements that do not describe the specific scientific contribution of the article.