The Journal of Heuristics provides a forum for advancing the state-of-the-art in the theory and practical application of techniques for solving problems approximately that cannot be solved exactly. It fosters the development, understanding, and practical use of heuristic solution techniques for solving business, engineering, and societal problems. It considers the importance of theoretical, empirical, and experimental work related to the development of heuristics.
The journal presents practical applications, theoretical developments, decision analysis models that consider issues of rational decision making with limited information, artificial intelligence-based heuristics applied to a wide variety of problems, learning paradigms, and computational experimentation.
Officially cited as: J Heuristics
- Provides a forum for advancing the state-of-the-art in the theory and practical application of techniques for solving problems approximately that cannot be solved exactly.
- Fosters the development, understanding, and practical use of heuristic solution techniques for solving business, engineering, and societal problems.
- Considers the importance of theoretical, empirical, and experimental work related to the development of heuristics.
- Manuel Laguna
- Publishing model
- Hybrid. Open Access options available
- 1.392 (2018)
- Impact factor
- 1.788 (2018)
- Five year impact factor
- 81 days
- Submission to first decision
- 374 days
- Submission to acceptance
- 40,299 (2019)
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.
Read recently published open access articles from the Journal of Heuristics.
The Journal of Heuristics follows general policies to submitted manuscripts that belong to the general areas of heuristic search for optimization, including but not limited to metaheuristics, hyperheuristics, and matheuristics.
About this journal
- Electronic ISSN
- Print ISSN
- Abstracted and indexed in
- ABS Academic Journal Quality Guide
- ACM Digital Library
- Current Contents/Engineering, Computing and Technology
- EBSCO Applied Science & Technology Source
- EBSCO Computer Science Index
- EBSCO Computers & Applied Sciences Complete
- EBSCO Discovery Service
- EBSCO Engineering Source
- EBSCO STM Source
- EI Compendex
- Gale Academic OneFile
- Gale InfoTrac
- Google Scholar
- Institute of Scientific and Technical Information of China
- Japanese Science and Technology Agency (JST)
- Journal Citation Reports/Science Edition
- OCLC WorldCat Discovery Service
- ProQuest ABI/INFORM
- ProQuest Advanced Technologies & Aerospace Database
- ProQuest Business Premium Collection
- ProQuest Central
- ProQuest Computer Science
- ProQuest SciTech Premium Collection
- ProQuest Technology Collection
- ProQuest-ExLibris Primo
- ProQuest-ExLibris Summon
- Research Papers in Economics (RePEc)
- Science Citation Index Expanded (SciSearch)