Development and Usage of Multi-criteria Decision Making/Analysis Methodologies with Fuzzy Sets for Guiding Strategic Development Decisions

  • Lanndon Anhao Ocampo

Student thesis: Doctoral Thesis


This portfolio consists of 19 papers published since 2016, revolving around a central theme of integrating the notion of ambiguity and imprecision in addressing the discrete case of multi- criteria decision making, popularly handled by multi-attribute decision-making (MADM) methods. The submitted papers in this portfolio contribute to the advancement of hybrid and extended tools for strategic decision making under conditions of multiple attributes while accounting for the inherent uncertainty in the decision-making process. These papers are making significant strides in demonstrating the application of these tools in strategic decision problems, with some of them previously unchartered in the literature. They are organized into three interrelated themes, each addressing distinct challenges and offering innovative methodologies applicable across diverse domains. In particular, these themes make contributions to the following agenda:

(1)The interdependencies among decision attributes
(2)The integration of uncertain information in generating a composite index
(3)Sorting of decision alternatives with imprecise input data

The papers comprising Theme 1 collectively address some prevailing characteristics in decision making by focusing on interdependencies, uncertainty, and complexity. The predominant approach espoused in papers [1], [2], [3], and [6] based on fuzzy DEMATEL-based ANP utilizes the ANP limiting supermatrix to generate priority vectors of decision criteria. This approach effectively manages interdependencies while accommodating the inherent ambiguity of decision- makers’ judgments. The papers [4], [5], and [7] introduce the concept of a nested sequential MADM problem, where solutions from one MADM problem become inputs to subsequent ones, with each problem allowing for the handling of interdependent attributes. The proposed frameworks in papers [4] and [5] integrate fuzzy AHP and fuzzy DEMATEL techniques to address uncertainty before deploying the ANP limiting supermatrix for generating the priority vector of decision attributes. The paper [7] offers a unique contribution to the theme by integrating the proposed intuitionistic FUCOM and intuitionistic fuzzy decision map extensions to handle nested sequential MADM problems. The application of these methodologies spans various domains, showcasing their adaptability and relevance in real-world problems.
The six papers in Theme 2 advance the methodologies for generating composite indexes, addressing uncertain and imprecise information across diverse applications. The integration of fuzzy variants of established MADM methods, such as AHP [8], BWM [9], [10], and FUCOM [11], allows for incorporating uncertain judgments into the index generation process. A novel simulation approach in the paper [12] solves a decision problem from randomly generated decision matrices extracted from decision-makers’ evaluations, resulting in probability distributions of composite indexes while capturing uncertainty without predefined parameters. To limit the cognitive workload of decision makers in judgment elicitations such as in paper [12], rough sets are deployed in paper [13] to handle uncertainty in indicator weighting and aggregation in an
innovative application. These methodologies are demonstrated in real-life applications in manufacturing [8], tourism [9], [10], [11], [12], and education [13] sectors.
The papers included in Theme 3 extend multiple criteria sorting methods by integrating fuzzy set extensions and novel approaches. Fuzzy set extensions, including intuitionistic fuzzy sets, Fermatean fuzzy sets, and 𝑞-rung orthopair fuzzy sets, enhance the ability of the sorting methods to handle uncertainty in the process. In paper [14], a novel multi-objective extension of PROMETHEE V, integrating fuzzy DEMATEL-ANP and fuzzy FlowSort, addresses a resource allocation problem derived from identifying the best class alternatives under interdependent criteria. An intuitionistic fuzzy extension of TOPSIS-Sort proposed in the paper [15] handles imprecise data in assessing customer exposure to COVID-19. The notion of Fermatean fuzzy sets is deployed to enhance CRITIC and CODAS-SORT methods, as demonstrated in the circular supply chain application in paper [16] and Education 4.0 implementation in paper [17]. Additionally, generalized 𝑞-ROFS is integrated into sorting methods to evaluate occupational hazards [18] and delay causes [19] in construction projects. These practical applications across diverse domains underscore the efficacy of the proposed methodological extensions.
The papers in the three themes collectively address complex strategic decision problems by introducing innovative methodologies that integrate fuzzy sets and their extensions, handle interdependent attributes, and enhance composite index generation and multiple criteria sorting. These methodologies find application in various domains, offering nuanced and informed decision strategies. The collaborations between analysts and domain experts highlighted in the papers underscore the importance of interdisciplinary research in addressing complex problems. Future research could explore advanced techniques for modeling interdependencies, efficient aggregation of indicators, and further integration of uncertainty in sorting methods. The presented contributions shape how intricate strategic problems are addressed and resolved, offering valuable insights for diverse sectors.

Keywords: multi-criteria decision making; fuzzy sets; uncertainty; strategic decisions; interdependencies; composite index; multiple criteria sorting
Date of Award8 Jan 2024
Original languageEnglish
Awarding Institution
  • University of Portsmouth
SupervisorDylan Jones (Supervisor) & Ashraf Labib (Supervisor)

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