M.Phil / MS
Permanent URI for this collectionhttps://repository.cuilahore.edu.pk/handle/123456789/52
This collection archives the complete set of theses produced by students of the COMSATS University Islamabad, Lahore Campus.
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Item Group Decision-Making Based on Linguistic Intuitionistic Fuzzy Numbers and Yager Weighted Aggregation Operator(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Aqsa; FA23-RMT-004; Dr. Atiq-ur-Rehman; LHR TP 9752We put forward two novel group decision making methods that utilize the propose Lin guistic Intuitionistic Fuzzy Yager Weighted Arithmetic Aggregation Operator for linguistic intuitionistic fuzzy numbers. The first proposed GDM addresses the situation where the weights of experts and attributes are fully understood; the second GDM approach that is being proposed takes into account the situation in which the weights of experts and the weights of attributes are entirely unknown. First, we propose new operational laws for LIFNs that are based on Yagers’ norm, specifically the addition operation and scalar mul tiplication operations for LIFNs can overcome the limitations of the current addition and scalar multiplication operations of LIFNs. After that, we put forward the LIFYWA AO of LIFN, relying on the proposed addition and scalar multiplication of LIFNs. We also demonstrate several characteristics of the suggested LIFYWA AO. Ultimately, we put for wardtwonewGDMmethodsofLIFNsbasedontheproposedLIFYWAAO.Thesuggested GDMmethodscanovercomethelimitations of current GDM approaches, which are unable to differentiate between the ranking orders of alternatives in certain cases.Item Consistency and Consensus Based Group Decision Making with Intuitionistic Multiplicative Preference Relations(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Ghaniya Irfan; FA23-RMT-010; Dr. Atiq-ur-Rehman; LHR TP 9758The primary objective of this research is to apply a distance-based consensus-reaching method within the framework of Intuitionistic Multiplicative Preference Relations to a group project investment decision. Experts provide pairwise preference matrices that capture their degrees of preference, non-preference, and hesitation. By measuring the distance between individual and collective matrices, the process evaluates the level of consensus and, if necessary, initiates iterative adjustments to align expert opinions. Ul timately, we use intuitionistic outranking flows to rank the alternative. This method effectively addresses uncertainty and inconsistency, thereby enhancing the robustness of group decisions in real-world investment contexts.Item AConsistency-Driven Group Decision Making Approach with Triangular Fuzzy Reciprocal Preference Relations(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Malaika Ali; FA23-RMT-021; Dr. Atiq-ur-Rehman; LHR TP 9768Triangular fuzzy reciprocal preference relations (TFRPRs) are one of the effective tools for expressing the fuzzy and uncertain preferences of decision makers in group decision making. The consistency of TFRPRs is a key prerequisite for reasonable and reliable de cision making. To this end, this study developed an improved multiplicative acceptable consistency group decision-making method based on TFRPRs. By analyzing the compo sition of TFRPRs, the multiplicative consistency index and the corresponding threshold are defined to measure whether TFRPRs have acceptable consistency. This consistency measure reflects the essential characteristics of triangular fuzzy numbers and fully consid ers the multiplicative consistency of the mode value and the multiplicative consistency of the geometric mean based on the central tendency. Then, three inconsistent TFRPR cases are analyzed, and an algorithm for solving TFRPR inconsistency based on mathematical derivation and linear programming model is proposed. Based on the multiplicative accep tance consistency (MACD) of TFRPRs, a MACD-IOWA is proposed to aggregate individ ual TFRPRs into group TFRPRs. The basic principle is that the higher the MACD value, the higher the decision maker’s weight. Finally, the feasibility and effectiveness of the proposed method are verified through case studies, comparative analysis and discussion.