This journal advances and promotes the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering.
The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.
- Advances and promotes the theory and applications of combinatorial optimization
- Deals with all theoretical, computational and applied aspects of combinatorial optimization
- Includes reviews of appropriate books and special issues of journals
- 100% of authors who answered a survey reported that they would definitely publish or probably publish in the journal again
Journal information
- Editor-in-Chief
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- My T. Thai
- Publishing model
- Hybrid. Open Access options available
Journal metrics
- 0.843 (2019)
- Impact factor
- 1.003 (2019)
- Five year impact factor
- 134 days
- Submission to first decision
- 243 days
- Submission to acceptance
- 69,621 (2019)
- Downloads
Latest issue
Latest articles
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Personalized manufacturing service composition recommendation: combining combinatorial optimization and collaborative filtering
Authors (first, second and last of 4)
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Eco-friendly container transshipment route scheduling problem with repacking operations
Authors (first, second and last of 4)
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A general framework for path convexities
Authors (first, second and last of 6)
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Maximum weight induced matching in some subclasses of bipartite graphs
Authors (first, second and last of 5)
Journal updates
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COVID-19 and impact on peer review
As a result of the significant disruption that is being caused by the COVID-19 pandemic we are very aware that many researchers will have difficulty in meeting the timelines associated with our peer review process during normal times. Please do let us know if you need additional time. Our systems will continue to remind you of the original timelines but we intend to be highly flexible at this time.
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SI: Combinatorial Optimization in Imaging Sciences
Guest Editors: Reneta Barneva (SUNY at Fredonia, USA) and Tibor Lukić (University of Novi Sad, Serbia)
Submission Deadline: October 15, 2020
The main objective of this special issue is to stimulate researchers to advance the theory of combinatorial optimization and its implementation in developing novel machine intelligence for imaging sciences. Authors are expected to propose original ideas and develop new techniques, structural results, and algorithms that improve researchers’ ability to solve practical problems.
About this journal
- Electronic ISSN
- 1573-2886
- Print ISSN
- 1382-6905
- Abstracted and indexed in
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- ABS Academic Journal Quality Guide
- ACM Digital Library
- CNKI
- Chimica
- Current Contents/Engineering, Computing and Technology
- Current Contents/Physical, Chemical and Earth Sciences
- DBLP
- Dimensions
- EBSCO Applied Science & Technology Source
- EBSCO Computers & Applied Sciences Complete
- EBSCO Discovery Service
- ECONIS
- EI Compendex
- Google Scholar
- INSPEC
- Institute of Scientific and Technical Information of China
- Japanese Science and Technology Agency (JST)
- Journal Citation Reports/Science Edition
- Mathematical Reviews
- Naver
- OCLC WorldCat Discovery Service
- ProQuest Advanced Technologies & Aerospace Database
- ProQuest Central
- ProQuest Engineering
- ProQuest Materials Science and Engineering Database
- ProQuest SciTech Premium Collection
- ProQuest Technology Collection
- ProQuest-ExLibris Primo
- ProQuest-ExLibris Summon
- SCImago
- SCOPUS
- Science Citation Index Expanded (SciSearch)
- UGC-CARE List (India)
- zbMATH
- Copyright information
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© Springer Science+Business Media, LLC, part of Springer Nature
