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I. Nishizaki and M. Sakawa, “Computational Methods through Genetic Algorithms for Obtaining Stackelberg Solutions to Two-Level Mixed Zero-One Programming Problems,” Cybernetics and Systems: An International Journal, Vol. 31, No. 2, 2000, pp. 203-221. doi:10.1080/019697200124892

has been cited by the following article:

• TITLE: Interactive Fuzzy Programming for Random Fuzzy Two-Level Integer Programming Problems through Fractile Criteria with Possibility

  AUTHORS: Masatoshi Sakawa, Takeshi Matsui

  KEYWORDS: Two-Level Integer Programming; Random Fuzzy Programming; Possibility; Fractile Criteria; Interactive Fuzzy Programming

  JOURNAL NAME: Applied Mathematics, Vol.4 No.8A, July 23, 2013

  ABSTRACT: This paper considers two-level integer programming problems involving random fuzzy variables with cooperative behavior of the decision makers. Considering the probabilities that the decision makers’ objective function values are smaller than or equal to target variables, fuzzy goals of the decision makers are introduced. Using the fractile criteria to optimize the target variables under the condition that the degrees of possibility with respect to the attained probabilities are greater than or equal to certain permissible levels, the original random fuzzy two-level integer programming problems are reduced to deterministic ones. Through the introduction of genetic algorithms with double strings for nonlinear integer programming problems, interactive fuzzy programming to derive a satisfactory solution for the decision maker at the upper level in consideration of the cooperative relation between decision makers is presented. An illustrative numerical example demonstrates the feasibility and efficiency of the proposed method.