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Classical, Rule-Based and Fuzzy Methods in Multi-Criteria Decision Analysis (MCDA) for Life Cycle Assessment

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Intelligent Computing (SAI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 858))

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Abstract

In every case of analysis of Life Cycle Assessment (LCA), there is the problem of comparing repeatedly contradictory criteria related to various types of impact factor. Traditional methods of LCA analysis are not capable of implementing such comparisons. This is a problem for multi-criteria evaluation. The analogy between the LCA and MCDM methodologies and the description of LCA as an MCDM problem for resolving the trade-offs between multiple environmental objectives are discussed in this study. The objective of the study is evaluation of opportunities of the use of knowledge-based methods to aggregate LCA results. We compare the results obtained with knowledge-based methods with results from a variety of specialized multi-criteria methods. The research used two classical multi–criteria decision making methods analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS), conventional (crisp) reasoning method and Mamdani’s fuzzy inference method. Classical rule-based approach flattens the results of assessments that practically are not suitable for LCA. The obtained results demonstrate that among the knowledge-based methods, crisp reasoning does not give satisfactory results. Mamdani’s method, AHP method and TOPSIS method allow diversity in the assessment but there are not solutions to assess the quality of these valuations.

This work is supported by the AGH University of Science and Technology statutory research No. 11/11.200.327.

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Authors and Affiliations

  1. Faculty of Management, AGH University of Science and Technology, Krakow, Poland

    Andrzej Macioł & Bogdan Rębiasz

Authors
  1. Andrzej Macioł
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  2. Bogdan Rębiasz
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Correspondence to Andrzej Macioł .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Department of Information Science, Saga University, Honjo, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

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Macioł, A., Rębiasz, B. (2019). Classical, Rule-Based and Fuzzy Methods in Multi-Criteria Decision Analysis (MCDA) for Life Cycle Assessment. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2018. Advances in Intelligent Systems and Computing, vol 858. Springer, Cham. https://doi.org/10.1007/978-3-030-01174-1_10

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