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 Yager’s Prioritized Model for Multi-Attribute Group Decision-Making Using p,q-Quasirung Orthopair Fuzzy Information(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Nisha Ashfaq; CIIT/SP24-RMT-014/LHR; Dr. Atiq-ur-Rehman; LHR TP 10075This study presents a multi-attribute group decision-making (MAGDM) approach based on Yager’s prioritized model under the framework of p,q-quasirung orthopair fuzzy sets (p,q-QROFSs). The proposed method effectively handles uncertainty and vagueness in decision-making environments while considering the priority relationships among decision attributes. Aggregation operators are developed to combine experts’ evaluations expressed in p,q-quasirung orthopair fuzzy information. The Yager prioritized mechanism is incorporated to reflect the relative importance of attributes and decision-makers. The effectiveness and practicality of the proposed approach are demonstrated through a numerical example and comparative analysis. Results indicate that the method provides reliable and flexible decision support for complex group decision-making problems involving uncertain information.Item Supplier Selection Using Multi-Attributive Border Approximation Area Comparison (MABAC) Model in Different Fuzzy Environments(Library Information Services COMSATS University Lahore Campus, 2024-03-17) Saleha Javed; SP23-RMT-029; Dr. Atiq-ur-Rehman; LHR TP 9565The main objective of this study is to develop a supplier selection approach that incorpo rates Multi-Attribute Border Approximation Area Comparison (MABAC) in three different fuzzy environments: Intuitionistic fuzzy MABAC, fuzzy MABAC, and Pythagorean fuzzy MABAC. By addressing uncertainties and assessments related to qualitative aspects such as quality, responsiveness, and reliability, the technique aims to optimize competing crite ria. Initially, the fuzzy MABAC methods utilize fuzzy evaluations to determine supplier ranks. Subsequently,fuzzy technologies that address imprecision in decision-making are integrated to assess the consistency of supplier rankings. The robustness of the approach is demonstrated by the consistent rankings of the best and worst suppliers across all three fuzzy environments. This innovative approach provides a reliable method for selecting sup pliers, ensuring that businesses can make informed decisions that consider both qualitative and quantitative factors even in uncertain circumstances.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.Item AHP Framework for Group Decision-Making under Hesitant Fuzzy Preference Relations(Library Information Services COMSATS University Islamabad Lahore Campus, 2025) Rumaisa Ahsan (FA23-RMT-034); Dr. Atiq-ur-Rehman; LHR TP 9780multi-criteria group decision-making problems with uncertainty based on hesitant fuzzy reference relations by the analytic hierarchy process. Although existing methods are advanced, they basically rely on the traditional preference models, which cannot effectively describe the hesitation and inconsistency that are seen naturally in an expert evaluation due to the limited characteristics of the existing methods. As the existing methods only rely on traditional preference models and cannot effectively describe the hesitation and inconsistency, this study introduces a TL-consistency based normalization strategy to normalize the incomplete hesitant fuzzy preference relations. The handling of group preferences involves a systematic process consisting of normalization, consistency assessment, agreement evaluation, and aggregation methods to ensure a consistent and analytically reliable representation of the group preference. In this phase, priority weights of the decision-makers from the previous two steps. The global alternatives rankings are derived by combining normalized hesitant fuzzy preference relations and forming a consistent evaluation matrix with a combined AHP. A numerical example illustrates the applicability of the approach, demonstrating the clarity and practical interpretability of the derived results and providing a case for generating strong decisions. This framework adds to the existing literature by increasing the possibility of consensus and consistency under conditions of ambiguity, subjectivity, and incomplete preference information in group decision-making settings.