Abstract
This chapter discusses non-compensatory methods with fuzzy indicator values. These methods are applicable to problems where we want to select an alternative among the available choices. The methods discussed in this chapter include fuzzy Lexicographic, fuzzy Dominance, fuzzy Max–Min, fuzzy Conjunctive Satisfying, and fuzzy Disjunctive Satisfying. In all methods, the assumption is that all indicator values are fuzzy. Non-compensatory methods have been developed using fuzzy ranking functions, and examples are provided for each method. Different ranking functions are used to solve the examples. In all examples, the results depend not only on the fuzzy values of the indicators but also on the ranking function. All non-compensatory methods are utilized in a fuzzy environment to choose one alternative from the available choices.
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A special thanks to the Iranian DEA society for their unwavering spiritual support and consensus in the writing of this book. Your invaluable support has been truly remarkable, and we are deeply grateful for the opportunity to collaborate with such esteemed professionals.
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Hosseinzadeh Lotfi, F., Allahviranloo, T., Pedrycz, W., Shahriari, M., Sharafi, H., Razipour GhalehJough, S. (2023). Non-Compensatory Methods in Uncertainty Environment. In: Fuzzy Decision Analysis: Multi Attribute Decision Making Approach. Studies in Computational Intelligence, vol 1121. Springer, Cham. https://doi.org/10.1007/978-3-031-44742-6_4
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DOI: https://doi.org/10.1007/978-3-031-44742-6_4
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