| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 500 | 26 | 29 | 12 |
Journal of Heuristics mainly tackles studies in Mathematical optimization, Heuristics, Metaheuristic, Algorithm and Heuristic (computer science). Journal of Heuristics connects research in Mathematical optimization with the related topic of Benchmark (computing). Heuristics research featured in Journal of Heuristics incorporates concerns from various other topics such as Genetic algorithm, Scheduling (computing), Job shop scheduling and Heuristic.
While Metaheuristic is the focus of the journal, it also provided insights into the studies of Simulated annealing, Combinatorial optimization and GRASP. The main emphasis of it is the research on GRASP, emphasizing the topic of Greedy randomized adaptive search procedure. Travelling salesman problem and Vehicle routing problem are some topics wherein Heuristic (computer science) research discussed in the journal have an impact.
The Travelling salesman problem works, particularly on 2-opt are tackled in the journal. The majority of Tabu search studies presented zero in on Guided Local Search. Local search (optimization) works presented in Journal of Heuristics have a specific focus on Iterated local search.
The published articles focus largely on the fields of Mathematical optimization, Heuristics, Metaheuristic, Tabu search and Heuristic (computer science). The research on Mathematical optimization featured in the most cited articles combines topics in other fields like Algorithm and Vehicle routing problem. Some problems in Metaheuristic that were presented in the journal papers overlapped with concepts under Simulated annealing and Combinatorial optimization.
Mathematical optimization, Heuristics, Heuristic (computer science), Integer programming and Optimization problem are among the topics commonly tackled in the journal. The journal explores topics in Mathematical optimization which can be helpful for research in disciplines like Constraint (information theory) and Benchmark (computing). It facilitates discussions on Benchmark (computing) that incorporate concepts from other fields like Dynamic programming, Metaheuristic and Job shop scheduling.
Concepts in Heuristic, as well as related topics in Response time, Supply and demand and Social planner, are covered in the Heuristics research presented in it. Journal of Heuristics explores research in Heuristic (computer science) alongside concepts in Approximation algorithm and other areas of study in Graph theory and Management science. While work presented in it provided substantial information on Optimization problem, it also covered topics in Discretization, Iterative method, Hamming distance and Proximity search.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Journal of Heuristics (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Journal of Heuristics (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 5.56% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 17.65% were posted by at least one author from the top 10 institutions publishing in the journal. Another 14.71% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 8.82% of all publications and 58.82% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
The research topics and discussions featured in the Journal of Heuristics not only provide a deeper understanding of mathematical optimizations and related fields, but they can also inspire potential career paths. For instance, the exploration and deep dive into metaheuristic, genetic algorithms, and simulated annealing may even inspire one to become a teacher or a thought leader within these disciplines.
If you're drawn towards the educational sector and wish to share knowledge on these fascinating topics, you could consider becoming a history teacher with a unique focus on the historical development of these scientific fields. If you’re based in Connecticut or considering a move, learn more about this career choice and the steps to become one here.
This career can be highly rewarding, especially when you inspire a new generation of thinkers and problem solvers. Getting a grasp on heuristic and related topics can help you provide students with insights into the intricacies of mathematical optimization, scheduling, and heuristic science. It’s not just about teaching the subject, but also sharing its potential impact on modern day computing applications.
Regardless of the career path you choose, the knowledge and understanding you gain from studies presented in the Journal of Heuristics can open up novel avenues and opportunities.
Javier Panadero;Jana Doering;Renatas Kizys;Angel A. Juan
(2020)Ankur Sinha;Zhichao Lu;Kalyanmoy Deb;Pekka Malo
(2020)Joaquín A. Pacheco;Manuel Laguna
(2020)Philippe Grangier;Michel Gendreau;Fabien Lehuédé;Louis-Martin Rousseau
(2021)Lorena S. Reyes-Rubiano;Laura Calvet;Angel A. Juan;Javier Faulin
(2020)Orlando Moreira;Merten Popp;Christian Schulz
(2020)Gleb Belov;Natashia L. Boland;Martin W. P. Savelsbergh;Peter J. Stuckey
(2020)Renata Turkeš;Kenneth Sörensen;Daniel Palhazi Cuervo
(2021)Jonatas B. C. Chagas;Jonatas B. C. Chagas;Julian Blank;Markus Wagner;Marcone J. F. Souza
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