Strategic Decision-Making Enhancement Framework (SDE-Framework): Leveraging Neutrosophic Logic and Fuzzy Mathematics for Optimized Outcomes in IT Management and Computational Systems
Manjula G. J.1, Shaik Khaja Mohiddin 2*, A. P. Pushpalatha3 , Vadali Srinivas4, M. Premalatha5, Sakthi R.6
1Department of Mathematics, Siddaganga Institute of Technology, Tumakuru – 572103, Karnataka, India.
2*Associate Professor, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur District, Andhra Pradesh - 522302, INDIA
3Department of Mathematics, Velammal College of Engineering and Technology, Madurai- 625009, Tamil Nadu, INDIA.
4Associate Professor, Department of Computer Science and Engineering, Vignan Institute of Technology and Science, Hyderabad - 508284, INDIA
5Department of Mathematics, Vel Tech Rangarajan Dr Sagunthala R & D Institute of Science and Technology, Chennai – 600062, Tamil Nadu, INDIA.
6Assistant Professor, Department of Mathematics, R.M.K College of Engineering and Technology, Puduvoyal – 601206, Chennai, Tamil Nadu, INDIA.
Emails: mail2mohiddin@kluniversity.in; gjm@sit.ac.in; app@vcet.ac.in; vsrinivas@vignanits.ac.in; drmpremalatha@veltech.edu.in; rsakth@gmail.com
Abstract
The created SDE-Framework combines neutronosophic logic and fuzzy mathematics in a novel method, aiming at facilitating more informed decision outcomes in computational systems and information technology management. This method hopes to aid in determining strategic solutions by controlling the expected sophistication and ambiguity in these two technologically dynamic industries. Neutronosophic logic divides data into three components: truth, indeterminacy, and falsity, build an exhaustive technique for addressing contradiction and indeterminacy. This significantly increases the method by enabling a more complete exploration of potential options with ambiguous and inadequate data. Second, the fuzzy mathematics gives a valuable contribution. It offers a refined method for managing the levels of probability and certainty through membership features, resulting in more exact and flexible evaluations. By the usage of such compared sophisticated mathematics concepts, SDE-Framework addresses potential decision-making scenarios by letting the computer formulates do the judgements for the determinable and in determinable explicit data. The subsequent crucial parameters are adopted to tolerance values: validity and responsibility, falseness foreach, indeterminacy magnitude to each, and truth value. This guarantees its combination of complexity supportive rand reading of actual surroundings.
Keywords: Adaptive Systems; Decision-Making; Fuzzy Mathematics; Management; Neutrosophic Logic; Uncertainty Handling