Abstract
Fuzzy relation equations and inequalities play an important role in many tools of fuzzy modelling and have been extensively studied. In many practical applications they are used as constraints in optimization. Algorithms for specific objective functions have been proposed by many authors. In this paper we introduce a method to convert a system of fuzzy relation constraints with max-t-norm composition to a linear constraint system by adding integer variables. A numerical example is provided to illustrate the proposed method.
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Lama, R., Asmuss, S. (2020). Optimization Under Fuzzy Max-t-Norm Relation Constraints. In: Kóczy, L., Medina-Moreno, J., Ramírez-Poussa, E., Šostak, A. (eds) Computational Intelligence and Mathematics for Tackling Complex Problems. Studies in Computational Intelligence, vol 819. Springer, Cham. https://doi.org/10.1007/978-3-030-16024-1_17
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DOI: https://doi.org/10.1007/978-3-030-16024-1_17
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