Fuzzy multiobjective mathematical programming in economic systems analysis: design and method

Economic systems analysis is a systems analysis technique of setting out the factors that have to be taken into account in making economic systems decisions. The inquiring and operational systems of the technique are almost exclusively designed for well-structured systems. In review of economic systems analysis against systems thinking, there is a growing tendency to discard the analytical approach as inappropriate for dealing with an ill-structured issue. Therefore, economic systems analysis needs both the inquiring and operational systems which are appropriate for ill-structured systems. The foregoing leads to the introduction of an extensive methodology. Mainly, the weakness of economic systems analysis methodology can be traced to the philosophical paradigm upon which the technique is based. In this study, four main aspects of both the inquiring and operational systems of economic systems analysis are being explored: (1) A new philosophical paradigm is proposed as the foundation of general methodology in place of the traditional Newtonian-Kantian inquiring system. (2) The new philosophical paradigm needs new problem formulation and analysis space; therefore, a multidimensional, synergetic, and autopoietic model is proposed for systems synthesis and systems analysis. (3) The new philosophical paradigm is characterized as a Singerian inquiry, and as a result, Marglin's multiobjective analysis is replaced by a Singerian multiobjective analysis. (4) Markov communication theory and fuzzy sets theory are proposed as tools for handling complexity. Markov communication theory and fuzzy sets theory are introduced for systems design and multiple objective analysis. This study reports on the first application of a Singerian fuzzy multiobjective mathematical algorithm in economic systems analysis, concluding that fuzzy systems theory, especially Markov communication theory, can realize approximate reasoning in economic systems analysis. Fuzzy modeling offers a deeper understanding of complexity and a means of expressing the insights that result from that understanding; moreover, it provides a means of incorporating subjectivity and adaptation. Therefore, fuzzy modeling increases the validity of the systems approach for dealing with ill-structured systems. The proposed method represents an important theoretical improvement of Marglin's approach. The results, however, also hold practical importance, for they are of practical interest to systems analysts who would improve systems design and multiobjective analysis.

Identiferoai:union.ndltd.org:pdx.edu/oai:pdxscholar.library.pdx.edu:open_access_etds-1470
Date01 January 1986
CreatorsXu, Li Da
PublisherPDXScholar
Source SetsPortland State University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceDissertations and Theses

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