85 research outputs found
Some remarks on optimality conditions for fuzzy optimization problems
In this article we present a new concept of stationary point for gH-differentiable fuzzy functions which generalize previous concepts that exist in the literature. Also, we give a concept of generalized convexity for gH-differentiable fuzzy functions more useful than level-wise generalized convexity (generalized convexity of the endpoint functions). Then we give optimatily conditions for fuzzy optimization problems.En este artículo presentamos un nuevo concepto de punto estacionario para funciones difusas gHdiferenciables que generalizan los conceptos previos que existen en la literatura. También damos un concepto de convexidad generalizada para funciones difusas gH-diferenciables más útil que los
basados en las funciones extremos. A partir de esos conceptos, damos condiciones de optimalidad para problemas de optimización difusos.Fondo Nacional de Desarrollo Científico y Tecnológico (Chile)Ministerio de Economía y CompetitividadFondo Europeo de Desarrollo Regiona
A survey on fuzzy fractional differential and optimal control nonlocal evolution equations
We survey some representative results on fuzzy fractional differential
equations, controllability, approximate controllability, optimal control, and
optimal feedback control for several different kinds of fractional evolution
equations. Optimality and relaxation of multiple control problems, described by
nonlinear fractional differential equations with nonlocal control conditions in
Banach spaces, are considered.Comment: This is a preprint of a paper whose final and definite form is with
'Journal of Computational and Applied Mathematics', ISSN: 0377-0427.
Submitted 17-July-2017; Revised 18-Sept-2017; Accepted for publication
20-Sept-2017. arXiv admin note: text overlap with arXiv:1504.0515
Note on ''Generalized Hukuhara differentiability of interval-valued functions and interval differential equations''
There are some mistakes in one of the papers of Luciano Stefanini and Barnabas Bede . In this article we are going to show that the case of proposition 24 in is incorrect. The corrected form is proposed in details
Symplectic connections and Fedosov's quantization on supermanifolds
A (biased and incomplete) review of the status of the theory of symplectic
connections on supermanifolds is presented. Also, some comments regarding
Fedosov's technique of quantization are made.Comment: Submitted to J. of Phys. Conf. Se
Necessary and sufficient conditions for interval-valued differentiability
This paper presents necessary and sufficient conditions for generalized Hukuhara differentiability of interval-valued functions and counterexamples of some equivalences previously presented in the literature, for which important results are based on. Moreover, applications of interval generalized Hukuhara differentiability are presented
New optimality conditions for multiobjective fuzzy programming problems
In this paper we study fuzzy multiobjective optimization problems de ned for n variables. Based on a new p-dimensional fuzzy stationary-point de nition, necessary e ciency conditions are obtained. And we prove that these conditions are also su cient under new fuzzy generalized convexity notions. Furthermore, the results are obtained under general di erentiability hypothesis.The research in this paper has been supported by Fondecyt-Chile, project 1151154 and by Ministerio de Economía y
Competitividad, Spain, through grant MINECO/FEDER(UE) MTM2015-66185-P
Numerical Solution of Fuzzy Fractional Differential Equation By Haar Wavelet
In this paper, we deal with a wavelet operational method based on Haar wavelet to solve the fuzzy fractional differential equation in the Caputo derivative sense. To this end, we derive the Haar wavelet operational matrix of the fractional order integration. The given approach provides an efficient method to find the solution and its upper bond error. To complete the discussion, the convergence theorem is subsequently expressed in detail. So far, no paper has used the Harr wavelet method using generalized difference and fuzzy derivatives, and this is the first time we have done so. Finally, the presented examples reflect the accuracy and efficiency of the proposed method
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