Strict and efficient solution methods for robust programming problems with ellipsoidal distributions under fuzziness

Authors:
Takashi Hasuike;Hideki Katagiri
Affiliations:
Graduate School of Information Science and Technology, Osaka University, 2-1, Yamadaoka, Suita, Osaka 565-0871, Japan.;Graduate School of Engineering, Hiroshima University, 1-4-1, Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8527, Japan
Venue:
International Journal of Knowledge Engineering and Soft Data Paradigms
Year:
2011

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Abstract

This paper considers robust programming problems with ellipsoidal distributions including fuzziness. Since this problem is not well-defined due to randomness and fuzziness, it is hard to solve it directly. Therefore, introducing chance constraints, fuzzy goal and necessity measures, the proposed model is transformed into the deterministic equivalent problems. Furthermore, since it is difficult to solve the main problem analytically and efficiently due to nonlinear programming, the solution method is constructed introducing an appropriate parameter and performing the equivalent transformations. By providing a numerical example, the feature of the proposed model is obtained.