## 2 Literature Review on FJSS and Smart Manufacturing  
The topic of scheduling flexible job-shop systems (FJSS) is a theme analyzed in the scientific literature as early as the 1980s, as demonstrated by a survey carried out on Elsevier's Scopus, the largest abstract and citation database of peer-reviewed literature. In order to identify publications on FJSS, an investigation using the string \"Scheduling flexible job-shop systems\" has been used. Only articles in which the string was found in the (1) article title, (2) abstract, or (3) keywords were analyzed (TITLE-ABS-KEY (scheduling AND flexible AND job-shop AND systems). The analysis on Scopus found 961 documents resulting from 1980 to 2021 (May 2021, period of investigation). The research highlighted a growth in the number of publications. Most of them have been published in 2020 (86 documents). Figure 2 shows the trend of publications over the years. The investigation on Scopus highlighted that the three most productive countries are China (287; 30%), the United States (123; 13%), and France (67; 7%). The result is not a surprise, because it only confirms that \"big\" countries in terms of population are obviously the most productive ones. Interestingly, other countries like Japan are also making great advances now in plant scheduling. A worthy study was proposed in 2019 by [PERSON] et al. [14] in which a hybrid cooperative coevolution algorithm (hCEA) for the minimization of fuzzy makespan was proposed. Furthermore, in 2015, [PERSON] et al. [15] developed hybrid genetic algorithms (HGA) and multiobjective HGA (Mo-HGA) to solve manufacturing scheduling problems. We have also investigated other parameters, as explained below. In particular, the analysis of documents by type pointed out the following distribution: articles (548; 57%), conference papers (346; 36%), conference reviews (44; 5%), books and chapters (8; 1%), reviews (8; 1%), and other (Letter. Editorial. Note 5; 1%). The analysis of documents by subject area highlighted that most of the publications (92%) belong to the following area: engineering (34%); computer science (29%); mathematics (10%); decision sciences (10%); business, management, and accounting (8%); and other (9%). The literature on the subject is certainly very extensive. Thus, we investigated a very precise aspect related to smart manufacturing. In the context of \"smart manufacturing\", we have selected 19 documents in line with our research goal. We selected the documents by examining the keywords and the field of application by analyzing all the documents  
Figure 2: Documents by year (source: Scopus). resulting from the investigation. Table 1 summarizes the number of documents by year and by type. According to the literature analysis, we have analyzed in detail the 19 documents as shown below. In particular, the following considerations emerged. Recently, [PERSON] et al. [16] developed an optimization algorithm to solve the FJSP in the context of a smart production plant. [PERSON] et al. [17] proposed a real-time scheduling model for the FJSP. [PERSON] et al. [18] proposed a genetic algorithm to solve the FJSP problem. In 2019, [PERSON] et al. [19] proposed a reusable scheduling problem decomposition framework for Industry 4.0 that facilitates agent-embedded optimization. In 2019, [PERSON] et al. [20] defined a simulation model of the smart flexible manufacturing system with interchangeable workplaces. A different point of view was introduced by [PERSON] et al. in 2019 [21]. They introduced an anarchic manufacturing model to evaluate the relative flexibility of a representative hierarchical system against an anarchic system in a job shop scenario. A survey on the scheduling in production in the context of Industry 4.0 systems was proposed by [PERSON] et al., 2019 [22]. [PERSON] and [PERSON] [23] presented a scheduling and dispatching approach for a flexible job shop incorporating travel times of autonomous guided vehicles. Some studies propose functional architecture for flexible manufacturing systems [24; 25].