N, visual perception, decision-making, prediction, and translation, among other people [4]. Over the final handful of years, the amount of academic publications regarding CI applied to FSC has rapidly elevated [5]. Within by far the most representative CI approaches applied to FSCs, we come across Neural Networks, Fuzzy Logic, Swarm Intelligence, or Probabilistic Reasoning. The scientific literature reports different research that aim to overview and order the application of CI solutions in various FSC stages. The number of CI solutions has led towards the emergence of study papers (published involving 2012 and 2020), which select a particular household of CI strategies and overview their application in certain FSC stages [2,62]. Even so, these papers focus on only a single or two households of CI procedures at most, and in the majority of cases, don’t cover all FSC stages. Hence, there is a lack of comprehensive studies that evaluation the application on the most significant families of CI methods in all FSC stages (from production to retail). In addition, handful of efforts happen to be made to classify FSC issues from a CI point of view. Hence, there’s no categorization on the typologies of FSC issues to assist determine how they can be modeled from a CI view (e.g., optimization, uncertain knowledge handling, reasoning) and what CI techniques might be most suitably applied to strategy them. Therefore, in spite of the progress created in organizing and systematizing the existing literature at the point where CI and FSCs meet, for the greatest of our expertise, no taxonomy has been proposed within this regard. Using the above-mentioned concepts in mind, we propose a novel taxonomy of FSC difficulties from a CI point of view. Specifically, we focus on the supply chain of agriculture, fish farming, and livestock. The latter is justified primarily based on the reality that these provide chains offer most of the meals consumed by the population of the globe [13] and, therefore, they’re by far the most studied and researched FSCs within the scientific and academic literature. The principle contributions of this article are: A new taxonomy that offers a comprehensive view of distinct FSC issues situated within the chain stages normally studied within the scientific literature (production, processing, distribution, and retail). This taxonomy Methiothepin Purity represents a brand new and broader proposal to be able to determine and define FSC difficulties which have been approached using CI inside the 4 aforementioned stages. In addition to, although some study articles have described diverse FSC challenges, their definitions are usually not unified and differ from 1 paper to another. Thus, this taxonomy also represents an effort to unify and consolidate definitions from the FSC complications available in the literature, which represents a worthwhile source of information for FSC researchers and practitioners operating in this domain. To classify the FSC issues from a CI perspective. This classification permits FSC problems to become mapped into widespread categories of issues in the CI domain. Therefore, we offer a framework that helps display the similarities and variations among FSC issues according to how they will be modeled below a CI point of view. For the greatest of our know-how, in this regard, no classification has been BI-409306 References previously proposed. To establish a set of suggestions for the use of CI within the FSC field. These guidelines aim to help FSC researchers and practitioners to identify which FSC difficulties could be addressed working with CI, as well as the most proper households of approaches to resolve them. Therefore, these guidelines represent a 1st.
