Advances in the Integration of Neutrosophic Sets with Metaheuristic Algorithms

Abstract

With the ongoing evolution and complexities of our contemporary world, the Neutrosophic Set (NS) was introduced to effectively cope with ambiguous and uncertain situations. It is a form of neutrosophy theory that explores the nature and scope of neutrality, as well as its interactions with other ideational spectra. Hence, it provides a powerful and broad foundation for numerous fields. Also, metaheuristic algorithms have emerged and proven their effectiveness in solving many optimization problems. Thus, incorporating NS with metaheuristic algorithms is a long-lasting method for resolving complicated optimization problems when there is ambiguous and insufficient data. The purpose of this survey is tripartite. Firstly, it starts with a review of the neutrosophic concepts. The survey's second section deals with metaheuristic algorithms. Finally, the most important part of the survey considers the integration between neutrosophic and metaheuristic algorithms. They are used in several fields, such as image segmentation, job shop scheduling, image clustering, and image classification. This research focuses on various ways of image processing that entail optimizing and processing images using neutrosophic sets and metaheuristics.