KKT optimality conditions for fuzzy optimization problems using $${H}^{1}$$ and $${H}^{2}$$ derivative
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Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s12597-024-00786-w.pdf
Reference22 articles.
1. Agarwal, D., Singh, P., El Sayed, M.A.: The Karush Kuhn Tucker (KKT) optimality conditions for fuzzy-valued fractional optimization problems. Math. Comput. Simul 205, 861–877 (2023). https://doi.org/10.1016/j.matcom.2022.10.024
2. Bede, B., Stefanini, L.: Generalized differentiability of fuzzy-valued functions. Fuzzy Sets Syst. 230, 119–141 (2013). https://doi.org/10.1016/j.fss.2012.10.003
3. Chalco-Cano, Y., Lodwick, W.A., Rufi, A., ́an-Lizana.: Optimality conditions of type kkt for optimization problem with interval-valued objective function via generalized derivative. Fuzzy Optim. Decis. Mak. 12(3), 305–322 (2013). https://doi.org/10.1007/s10700-013-9156y
4. Chalco-Cano, Y., Rufi ́an-Lizana, A., Rom ́an-Flores, H., Jim ́enez-Gamero, M.-D.: Calculus for interval-valued functions using generalized hukuhara derivative and applications. Fuzzy Sets Syst. 219, 49–67 (2013). https://doi.org/10.1016/j.fss.2012.12.004
5. Dubois, D., Prade, H.: Towards fuzzy differential calculus part 1: integration of fuzzy mappings. Fuzzy Sets Syst. 8(1), 1–17 (1982). https://doi.org/10.1016/0165-0114(82)90025-2
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