ORIGINAL_ARTICLE
On Bottleneck Product Rate Variation Problem with Batching
The product rate variation problem minimizes the variation in the rate at which different models of a common base product are produced on the assembly lines with the assumption of negligible switch-over cost and unit processing time for each copy of each model. The assumption of significant setup and arbitrary processing times forces the problem to be a two phase problem. The first phase determines the size and the number of batches and the second one sequences the batches of models. In this paper, the bottleneck case i.e. the min-max case of the problem with a generalized objective function is formulated. A Pareto optimal solution is proposed and a relation between optimal sequences for the problem with different objective functions is investigated.
http://ijo.iaurasht.ac.ir/article_514134_66aee2e924eb1b0beb59235054f07992.pdf
2013-07-01T11:23:20
2018-08-14T11:23:20
477
491
Product rate variation problem
batching
sequencing problem
nonlinear integer programming
Shree
Khadka
shreeramkhadka@gmail.com
true
1
Central Department of Mathematics, Tribhuvan University, Kathmandu, Nepal
Central Department of Mathematics, Tribhuvan University, Kathmandu, Nepal
Central Department of Mathematics, Tribhuvan University, Kathmandu, Nepal
LEAD_AUTHOR
Tanka
Dhamala
dhamala@yahoo.com
true
2
Central Department of Mathematics, Tribhuvan University, Kathmandu, Nepal
Central Department of Mathematics, Tribhuvan University, Kathmandu, Nepal
Central Department of Mathematics, Tribhuvan University, Kathmandu, Nepal
AUTHOR
ORIGINAL_ARTICLE
Mapping Sequence diagram in Fuzzy UML to Fuzzy Petri Net
This ability in fuzzy UML, practically leaves the customers and market’s need without response in this important and vital area. Here, the available sequence diagrams in fuzzy UML will map into fuzzy Petri net. However, the formal models ability will be added to the Semi-formal fuzzy UML. This formalization will add the automatic processing ability to the Semi-formal fuzzy UML. Further more, the other advantages of this mapping is: access to non-functional parameters such as reliability automatically to the considering systems, study the verification of the designed plan and also decrease the expenses because of satiety to make lab sample before its implementation. Using the fuzzy UML mapping into fuzzy Petri net in control, critical and real-time systems will be more applicable.
http://ijo.iaurasht.ac.ir/article_514136_8e2d23e5ff6ba2e807b4dbea0b3bd9b1.pdf
2013-07-01T11:23:20
2018-08-14T11:23:20
492
505
non-functional parameters
fuzzy UML
sequence diagram
fuzzy Petri net
Formalization
E.
Akbari
true
1
Department of Mathematics, Islamic Azad University, Sari Branch, Sari, Iran
Department of Mathematics, Islamic Azad University, Sari Branch, Sari, Iran
Department of Mathematics, Islamic Azad University, Sari Branch, Sari, Iran
AUTHOR
R.
Noorian Talooki
true
2
Department of Computer Engineering, Islamic Azad University, Sari Branch, Sari, Iran
Department of Computer Engineering, Islamic Azad University, Sari Branch, Sari, Iran
Department of Computer Engineering, Islamic Azad University, Sari Branch, Sari, Iran
AUTHOR
H.
Motameni
motameni@iausari.ac.ir
true
3
Department of Computer Engineering, Islamic Azad University, Sari Branch, Sari, Iran
Department of Computer Engineering, Islamic Azad University, Sari Branch, Sari, Iran
Department of Computer Engineering, Islamic Azad University, Sari Branch, Sari, Iran
LEAD_AUTHOR
ORIGINAL_ARTICLE
On the averaging of differential inclusions with Fuzzy right hand side with the average of the right hand side is absent
In this article we consider the averaging method for differential inclusions with fuzzy right-hand side for the case when the limit of a method of an average does not exist.
http://ijo.iaurasht.ac.ir/article_514137_d97144096845e36718c73422f2f61fec.pdf
2013-07-01T11:23:20
2018-08-14T11:23:20
506
517
differential inclusion
averaging method
fuzzy set
R-solution
Andrej
Plotnikov
a-plotnikov@ukr.net
true
1
Odessa State Academy of Civil Engineering and Architecture, Odessa, Ukraine
Odessa State Academy of Civil Engineering and Architecture, Odessa, Ukraine
Odessa State Academy of Civil Engineering and Architecture, Odessa, Ukraine
LEAD_AUTHOR
Tatyana
Komleva
true
2
Odessa State Academy of Civil Engineering and Architecture, Odessa, Ukraine
Odessa State Academy of Civil Engineering and Architecture, Odessa, Ukraine
Odessa State Academy of Civil Engineering and Architecture, Odessa, Ukraine
AUTHOR
Lilia
Plotnikova
true
3
Odessa National Polytechnic University, Odessa, Ukraine
Odessa National Polytechnic University, Odessa, Ukraine
Odessa National Polytechnic University, Odessa, Ukraine
AUTHOR
ORIGINAL_ARTICLE
Analytic-Approximate Solution For An Integro- Differential Equation Arising In Oscillating Magnetic Fields Using Homotopy Analysis Method
In this paper, we give an analytical approximate solution for an integro- differential equation which describes the charged particle motion for certain configurations of oscillating magnetic fields is considered. The homotopy analysis method (HAM) is used for solving this equation. Several examples are given to reconfirm the efficiency of these algorithms. The results of applying this procedure to the integro-differential equation with time-periodic coefficients show the high accuracy, simplicity and efficiency of this method.
http://ijo.iaurasht.ac.ir/article_514138_83b91e496581c65b2416ec737b16ac35.pdf
2013-07-01T11:23:20
2018-08-14T11:23:20
518
535
Homotopy analysis method
integro-differential equations
approximate-analytic solution
homotopy-derivative
Homotopy perturbation method
H.
Saberi-Nik
saberi_hssn@yahoo.com
true
1
Department of Applied Mathematics, Ferdowsi University of Mashhad, P.O. Box 1159, Mashhad, Iran.
Department of Applied Mathematics, Ferdowsi University of Mashhad, P.O. Box 1159, Mashhad, Iran.
Department of Applied Mathematics, Ferdowsi University of Mashhad, P.O. Box 1159, Mashhad, Iran.
LEAD_AUTHOR
S.
Effati
true
2
Department of Applied Mathematics, Ferdowsi University of Mashhad, P.O. Box 1159, Mashhad, Iran.
Department of Applied Mathematics, Ferdowsi University of Mashhad, P.O. Box 1159, Mashhad, Iran.
Department of Applied Mathematics, Ferdowsi University of Mashhad, P.O. Box 1159, Mashhad, Iran.
AUTHOR
R.
Buzhabadi
true
3
Department of Applied Mathematics, Ferdowsi University of Mashhad, P.O. Box 1159, Mashhad, Iran.
Department of Applied Mathematics, Ferdowsi University of Mashhad, P.O. Box 1159, Mashhad, Iran.
Department of Applied Mathematics, Ferdowsi University of Mashhad, P.O. Box 1159, Mashhad, Iran.
AUTHOR