SOLUTION OF FUZZY DIFFERENTIAL EQUATIONS UNDER GENERALIZED DIFFERENTIABILITY BY ADOMIAN DECOMPOSITION METHOD
T.
Allahviranloo
Department of Mathematics, Science and Research Branch, Islamic Azad
University,Tehran, 14778, Iran
author
L.
Jamshidi
Department of Mathematics, Science and Research Branch, Islamic Azad
University,Tehran, 14778, Iran
author
text
article
2009
eng
Adomian decomposition method has been applied to solve many functional equations so far. In this article, we have used this method to solve the fuzzy differential equation under generalized differentiability. We interpret a fuzzy differential equation by using the strongly generalized differentiability. Also one concrete application for ordinary fuzzy differential equation with fuzzy input data are given.
Iranian Journal of Optimization
Islamic Azad University, Rasht Branch
2008-5427
01
v.
2
no.
2009
57
75
http://ijo.iaurasht.ac.ir/article_513238_dae63f310440b6654e11f0bfff9f25fe.pdf
DESIGNING AN OPTIMIZATION MODEL FOR PREVENTING THE WASTE TIME IN THE ACTIVITY CYCLE OF AN ORGANIZATION
M.
Taleghani
Department of post – graduate Islamic Azad university, Rasht, Iran
author
Y.
Modabbernia
Department of post – graduate Islamic Azad university, Rasht, Iran
author
text
article
2009
eng
This article proposes an optimization model for preventing the waste of time in the educational and research activities' cycle of an organization such as a university. For this purpose and in order to increase efficiency and prevent the waste of time; the graph theory models have been used. The educational and research activities diagrams of a supposed university is drawn by the use of graphs theory model, and then these graphs are analyzed, then in order to design a model, the units, activities and the time of doing each activity are symbolized, and the collected data are presented in the form of matrix. In this article two procedures are suggested for optimization; using subgraphs for every activity cycle in order to shorten the activity cycles and minimizing the time of doing each work. The algorithm of time minimizing is based on recognizing and determining the edges with the most weight as the maximum time. Also the influential factors on the waste of time in activity cycle are recognized and then replaced or omitted.
Iranian Journal of Optimization
Islamic Azad University, Rasht Branch
2008-5427
01
v.
2
no.
2009
76
89
http://ijo.iaurasht.ac.ir/article_513239_a829e56ed825af242a8931889c6efcdc.pdf
THE USE OF SEMI INHERITED LU FACTORIZATION OF MATRICES IN INTERPOLATION OF DATA
MOHAMMAD ALI
FARIBORZI ARAGHI
Department of mathematics, Islamic Azad University,Central Tehran Branch,
Tehran, Iran
author
Amir
Fallahzadeh
Department of mathematics, Islamic Azad University,Central Tehran Branch,
Tehran, Iran
author
text
article
2009
eng
The polynomial interpolation in one dimensional space R is an important method to approximate the functions. The Lagrange and Newton methods are two well known types of interpolations. In this work, we describe the semi inherited interpolation for approximating the values of a function. In this case, the interpolation matrix has the semi inherited LU factorization.
Iranian Journal of Optimization
Islamic Azad University, Rasht Branch
2008-5427
01
v.
2
no.
2009
90
106
http://ijo.iaurasht.ac.ir/article_513241_6b96aef6042079838dadd9287db3e2ba.pdf