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@article{193747,
        author = {R.Keerthika and K.K.Myithili},
        title = {Task Completion And Allocation Of Task Assignment To Multi-Tasking Robots Using IFk-PHG},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {1598-1604},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=193747},
        abstract = {An extension of a graph in which hyperedges can join subsets of vertices instead of simply pairs is called a hypergraph. The edges in a hypergraph are arbitrary, non-empty sets of vertices. Similar to traditional graphs, hypergraphs facilitate higher-order interactions in communication and social networks. In this paper, we explore the structural properties of Intuitionistic Fuzzy k-partite Hypergraphs (IFk-PHGs). Specifically, we analyze the lower and upper truncation of IFk-PHG, as well as different types of intersections, including intersecting IFk-PHG, K-intersecting IFk-PHG and strongly intersecting IFk-PHG. Furthermore, as long as an IFk-PHG is K-intersecting, we can conclude that it is strongly intersecting.  A multi-tasking robot is a type of robotic system that is capable of performing multiple tasks or functions without the need for manual intervention or reprogramming between tasks. These robots are designed to be skilled and flexible allowing them to switch between different tasks seamlessly. Intuitionistic Fuzzy parameters enable flexible, advanced representation of multi-tasking robot systems, guiding decision-making processes like task allocation, task completion and coordination in uncertain situations addressing uncertainty in robot capabilities and task suitability. This work proposes how task is allocated to robots using IFk-PHG and which robot can complete the task quickly. The task completion of the robots can be done using score function formula.},
        keywords = {},
        month = {March},
        }