# Graph-Based Modeling in Shop Scheduling Problems: Review and Extensions
## 2 Materials and Methods
To give a brief context to the depth and variety of our dataset, the breakdown analysis by year, publisher, and the quality of the journal are represented for the 143 total papers. Figure 2 shows the dataset breakdown by year (2015 to 2020) where a relatively consistent number of publications per year is observed in this dataset. This could potentially refer to a steady interest in the topic. Note that a couple of references in our dataset were officially published within January and February of 2021, counting in the 2020 category. Figure 3 summarizes the breakdown of collected papers by their publisher, i.e., each paper was labeled with its parent publishing organization. The 'Other' category includes publishers that only appeared once in our dataset. For example, World Scientific, Research India Publications, Genamatics, Scimago, MIT Press, and seven other publishers. Elsevier is the most popular publisher in the overlapped domains of graph theory and shop scheduling problem. It published 41% of our dataset followed by SpringerLink publishing 18% of the collected papers. Figure 1: The systematic search process utilized in this paper. Furthermore, a subjective categorization over the quality of the target journals is proposed in Figure 4. The prestige sorting was done by observing each journal's EigenFactor and latest ABDC score [29; 30]. Journals were sorted into three tiers of prestige: premier (>90 th percentile in EigenFactor or 'A*' rating in ABDC), major (>50 th percentile in EigenFactor or 'A' rating in ABDC), and other (journals that did not meet premier or major criteria). According to our definition of Premier/Major/Other, the 'Premier' category includes the least number of journals (due to the strictest criteria) and the 'Other' category contains the greatest number of journals (having the loosest criteria). However, the distribution of our dataset does not comply with this order, i.e., the 'Major' journals are observed the most frequently in our dataset (Figure 4). An optimistic reason for this observation can be that this area of research keeps attracting a relatively great attention by more prestigious journals due to its potential applicability. Another metric which might be able to describe the impact of the collected references is the number of citations. The number of citations for all references in the dataset was up to date as of April 2021. It should be noted that our data collection methodology had no conscious preference towards more highly cited papers, leaving this dataset unbiased with this regard. This information is distilled into three values of interest below in Table 2.  
Figure 4: Breakdown of dataset papers by journal prestige. Figure 3: Breakdown of dataset by publisher. Figure 2: Breakdown of dataset by year of publications. The total number of citations (2729) for all 143 papers can imply the validity of our dataset. Since papers published more recently have less chance to be cited, we normalized the citation data by considering the number of 'citations per year' for each paper as a relatively fair baseline to compare. The average of 5.5 'citations per year 'for papers can imply a positive perspective in this research field. The most cited paper per year has earned 92 citations since 2018 and was published in a 'Premier' journal [31]. An interesting result observed in the top 10% of most cited papers per year is that out of 14 papers, 5 are published in 'Premier' journals, six in 'Major', and three in 'Other'.