2018
8
2
30
0
Multiobjective Imperialist Competitive Evolutionary Algorithm for Solving Nonlinear Constrained Programming Problems
2
2
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 wellknown NPhard nonlinear constrained optimization functions, and the empirical evidence suggests that the proposed method is robust, efficient, and generic.
1

67
72


chunan
liu
Department of Mathematics, Baoji University of Arts and Sciences, Baoji 721013, P. R. China
Department of Mathematics, Baoji University
Iran
654252583@qq.com
Multiobjective optimization
Imperialist competitive evolutionary algorithm
nonlinear constrained optimization
optimal solution
TwoWarehouse Inventory Model for Deteriorating Items with TimeDependent Demand and Partial Backlogging Under Inflation
2
2
This paper deals with a twowarehouse inventory model for deteriorating items with time dependent demand and partial backlogging under inflation. It is assumed that deterioration of items follows twoparameter 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.
1

73
88


Sanjay
Singh
Department of Mathematics,
Raj Kumar Goel Institute of Technology, Ghaziabad, Uttat Pradesh, India.
Department of Mathematics,
Raj Kumar Goel
Iran
ssingh_hapur@yahoo.co.in


Seema
Sharma
Department of Mathematics and Statistics,
GKV. University, Haridwar, Uttarakhand, India
Department of Mathematics and Statistics,
GKV.
Iran
dikshitseema@yahoo.com


Shiv
Pundir
Department of Mathematics,
CCS University, Meerut, UP. India.
Department of Mathematics,
CCS University,
Iran
shivrajpundir@gmail.com
Twowarehouse
deterioration
partial backlogging
inflation
A New Method based on Intelligent Water Drops for Multicast Routing in Wireless Mesh Networks
2
2
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 subproblems in sequence. In this paper, the aim is to propose a new method based on intelligent water drops that solve subproblem 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 LCMRMC.
1

89
99


shiva
zendehdelan
department of computer engineering,central Tehran branch, Islamic azad university, Tehran Iran
department of computer engineering,central
Iran
sh.zendedelan@gmail.com


Reza
Ravanmehr
department of computer engineering, central Tehran branch, Islamic azad university, Tehran, Iran.
department of computer engineering, central
Iran
shivazendecomputerengineer@gmail.com


babak
vaziri
department of computer engineering, Central Tehran branch, Islamic Azad university, Tehran, Iran
department of computer engineering, Central
Iran
babak@hotmail.com
wireless mesh networks
multicast routing
channel assignment
multi radio multi channel
intelligent water drops
Purchasing Inventory Models for Deteriorating Items with Linear Demand and Shortages  in Third Order Equation
2
2
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
1

101
114


Sivashankari
C.K.
A2/S3 Manasaravar Apartment, West Mada Street, Chennai 600 062
A2/S3 Manasaravar Apartment, West Mada Street,
Iran
vinangi.ck@gmail.com
Inventory
Deteriorating
linear demand
cycle time
shortages and sensitivity analysis
Application of Stochastic Optimal Control, Game Theory and Information Fusion for Cyber Defense Modelling
2
2
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.
1

115
124


Maryam
Mohaghegh Tabar
Department of Sciences,Fouman and Shaft Branch,Islamic Azad University, Fouman, Iran
Department of Sciences,Fouman and Shaft Branch,Isl
Iran
m.mohagheghtabar@fshiau.ac.ir


Ali
Mahmoodi
Department of Computer Engineering, Ozyegin University, Istanbul, Turkey
Department of Computer Engineering, Ozyegin
Iran
ali.nehrani@ozu.edu.tr
Stochastic optimal control
Information fusion
Game Theory
Cyber defense
Robust Optimization
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
2
2
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.
1

125
132


Esmat
Nikbakht
Dezful Branch, Islamic Azad University
Dezful Branch, Islamic Azad University
Iran
ef.nikbakht@yahoo.com
Matrix function
Matrix polynomial
Minimal polynomial
Characteristic polynomial
Eigenvalue decomposition
Jordan canonical form