Islamic Azad University, Central tehran Branch
International Journal of Mathematical Modelling & Computations
2228-6225
2228-6233
8
2 (SPRING)
2018
04
01
Multiobjective Imperialist Competitive Evolutionary Algorithm for Solving Nonlinear Constrained Programming Problems
67
72
EN
chunan
liu
Department of Mathematics, Baoji University of Arts and Sciences, Baoji 721013, P. R. China
654252583@qq.com
Nonlinear constrained programing problem (NCPP) has been arisen in diverse range of sciences such as portfolio, economic management etc.. In this paper, a multiobjective imperialist competitive evolutionary algorithm for solving NCPP is proposed. Firstly, we transform the NCPP into a biobjective optimization problem. Secondly, in order to improve the diversity of evolution country swarm, and help the evolution country swarm to approach or land in the feasible region of the problem, three kinds of different methods of colonies moving toward their relevant imperialist are given. Thirdly, the new operator for exchanging position of the imperialist and colony is given similar as a recombination operator in genetic algorithm to enrich the exploration and exploitation abilities of the proposed algorithm. At last, the new approach is tested on two well-known NP-hard nonlinear constrained optimization functions, and the empirical evidence suggests that the proposed method is robust, efficient, and generic.
Multiobjective optimization,Imperialist competitive evolutionary algorithm,nonlinear constrained optimization,optimal solution
http://ijm2c.iauctb.ac.ir/article_663817.html
http://ijm2c.iauctb.ac.ir/article_663817_64744cb2042ec14fc5665c28b2055c7e.pdf
Islamic Azad University, Central tehran Branch
International Journal of Mathematical Modelling & Computations
2228-6225
2228-6233
8
2 (SPRING)
2018
04
01
Two-Warehouse Inventory Model for Deteriorating Items with Time-Dependent Demand and Partial Backlogging Under Inflation
73
88
EN
Sanjay
Singh
Department of Mathematics,
Raj Kumar Goel Institute of Technology, Ghaziabad, Uttat Pradesh, India.
ssingh_hapur@yahoo.co.in
Seema
Sharma
Department of Mathematics and Statistics,
GKV. University, Haridwar, Uttarakhand, India
dikshitseema@yahoo.com
Shiv
Raj
Pundir
Department of Mathematics,
CCS University, Meerut, UP. India.
shivrajpundir@gmail.com
This paper deals with a two-warehouse inventory model for deteriorating items with time dependent demand and partial backlogging under inflation. It is assumed that deterioration of items follows two-parameter Weibull distribution and demand rate varies exponentially with time. Shortages are allowed and partial backlogging depends on waiting time of next replenishment. A numerical example is provided to illustrate the considered model. Further, sensitivity analysis has also been made to show the behavior of the present model.
Two-warehouse,deterioration,partial backlogging,inflation
http://ijm2c.iauctb.ac.ir/article_663813.html
http://ijm2c.iauctb.ac.ir/article_663813_5e9c7dc976856684f1717322dccdfc85.pdf
Islamic Azad University, Central tehran Branch
International Journal of Mathematical Modelling & Computations
2228-6225
2228-6233
8
2 (SPRING)
2018
04
01
A New Method based on Intelligent Water Drops for Multicast Routing in Wireless Mesh Networks
89
99
EN
shiva
zendehdelan
department of computer engineering,central Tehran branch, Islamic azad university, Tehran Iran
sh.zendedelan@gmail.com
Reza
Ravanmehr
department of computer engineering, central Tehran branch, Islamic azad university, Tehran, Iran.
shivazendecomputerengineer@gmail.com
babak
vaziri
department of computer engineering, Central Tehran branch, Islamic Azad university, Tehran, Iran
babak@hotmail.com
In recent years a new type of wireless networks named wireless mesh networks has drawn the attention of researchers. In order to increase the capacity of mesh network, nodes are equipped with multiple radios tuned on multiple channels emerging multi radio multi channel wireless mesh networks. Therefore, the main challenge of these networks is how to properly assign the channels to the radios. On the other hand, multicast routing makes the delivery of the same content possible from one source to several destinatios. For example, video confereceing and distant learning are some applications of multicast routing. The problem of multicast routing coupled with channel assignment is known as an NP hard problem, and hence operation research based methods are not scalable. Most of exsisting heuristic methods for this problem solve two aformetnioned sub-problems in sequence. In this paper, the aim is to propose a new method based on intelligent water drops that solve sub-problem channel assignemt in conjuction with multicast roung. Simulation results demonstrate the improvement of throghput, end to end delay, and packet delivery ratio compared to CLLO, CAMF, and LC-MRMC.
wireless mesh networks,multicast routing,channel assignment,multi radio multi channel,intelligent water drops
http://ijm2c.iauctb.ac.ir/article_663814.html
http://ijm2c.iauctb.ac.ir/article_663814_922de485d20106f18bd2652b7dc1fba1.pdf
Islamic Azad University, Central tehran Branch
International Journal of Mathematical Modelling & Computations
2228-6225
2228-6233
8
2 (SPRING)
2018
04
01
Purchasing Inventory Models for Deteriorating Items with Linear Demand and Shortages - in Third Order Equation
101
114
EN
Sivashankari
C.K.
A2/S3 Manasaravar Apartment, West Mada Street, Chennai 600 062
vinangi.ck@gmail.com
In this paper, an purchasing inventory model for deteriorating items is developed with a linear, positive trend in demand, allowing inventory shortages and backlogging. It is assumed that the goods in the inventory deteriorate over time at a constant rate . Two models are developed for two operational policies. The first policy covers the case that the inventory model with linear demand for deteriorative items and the second policy covers the case that the inventory model with linear demand for deteriorative items and shortages. Mathematical model is developed for each model to reduce the third order equation and the optimal cycle time and inventory lot size which minimizes the total cost is derived. Illustrative example is provided for each model. In each model, sensitivity analysis is performed to show how the optimal values of the policy variables in the model change as various model parameters are changed. The validation of result in this model was coded in Microsoft Visual Basic 6.0
Inventory,Deteriorating,linear demand,cycle time,shortages and sensitivity analysis
http://ijm2c.iauctb.ac.ir/article_663815.html
http://ijm2c.iauctb.ac.ir/article_663815_ad417360fa2d9e5d0b4e0c4dce746a60.pdf
Islamic Azad University, Central tehran Branch
International Journal of Mathematical Modelling & Computations
2228-6225
2228-6233
8
2 (SPRING)
2018
04
01
Application of Stochastic Optimal Control, Game Theory and Information Fusion for Cyber Defense Modelling
115
124
EN
Maryam
Mohaghegh Tabar
Department of Sciences,Fouman and Shaft Branch,Islamic Azad University, Fouman, Iran
m.mohagheghtabar@fshiau.ac.ir
Ali
Mahmoodi
Department of Computer Engineering, Ozyegin University, Istanbul, Turkey
ali.nehrani@ozu.edu.tr
The present paper addresses an effective cyber defense model by applying information fusion based game theoretical approaches. In the present paper, we are trying to improve previous models by applying stochastic optimal control and robust optimization techniques. Jump processes are applied to model different and complex situations in cyber games. Applying jump processes we propose some models for cyber battle spaces. The resulted stochastic models are solved by applying stochastic optimal control methods. A robust optimization technique is proposed to obtain robust estimations in the case of lack of complete data. We address reinforcement learning throughout the by stochastic optimal control formulation. Previous models are improved by applying optimal control approaches to overcome the issue of time steps in game theory based approaches in which times steps cause limitations by considering the cases that may take longer times. Two adaptation methods are proposed in incomplete information cases.
Stochastic optimal control,Information fusion,Game Theory,Cyber defense,Robust Optimization
http://ijm2c.iauctb.ac.ir/article_663816.html
http://ijm2c.iauctb.ac.ir/article_663816_c6671296f32c214f15ca60154c650099.pdf
Islamic Azad University, Central tehran Branch
International Journal of Mathematical Modelling & Computations
2228-6225
2228-6233
8
2 (SPRING)
2018
04
01
Determination of a Matrix Function in the Form of f(A)=g(q(A)) Where g(x) Is a Transcendental Function and q(x) Is a Polynomial Function of Large Degree Using the Minimal Polynomial
125
132
EN
Esmat
Nikbakht
Dezful Branch, Islamic Azad University
ef.nikbakht@yahoo.com
Matrix functions are used in many areas of linear algebra and arise in numerical applications in science and engineering. In this paper, we introduce an effective approach for determining matrix function f(A)=g(q(A)) of a square matrix A, where q is a polynomial function from a degree of m and also function g can be a transcendental function. Computing a matrix function f(A) will be time- consuming and difficult if m is large. We propose a new technique which is based on the minimal polynomial and characteristic polynomial of the given matrix A, which causes, to reduce the degree of polynomial function significantly. The new approach has been tested on several problems to show the efficiency of the presented method. Finally, the application of this method in state space and matrix quantum mechanics is highlighted.
Matrix function,Matrix polynomial,Minimal polynomial,Characteristic polynomial,Eigenvalue decomposition,Jordan canonical form
http://ijm2c.iauctb.ac.ir/article_663818.html
http://ijm2c.iauctb.ac.ir/article_663818_6475c08c7ca652203e0d3bfe5fe2be56.pdf