Purpose: The main objective of this paper is, to determine the optimal no. of technicians’ men in a workshop crew of an Industrial System.   Theoretical framework: The purpose of applying these tools is to explore their ability to reduce costs and improvements that can be obtained in the process of providing services to the end customer.   Design/methodology/approach: The literature structure review was built from analyzing 12 of scientific papers and books, from web sciences and the Elsevier database. The papers were analyzed from descriptive, methodologic, and citation characteristics.   Finding:  By applying the equation model of the paper, the optimal no. of technician men in the crew of the workshop can be determined when

In order to select the optimal tracking of fast time variation of multipath fast time variation Rayleigh fading channel, this paper focuses on the recursive least-squares (RLS) and Extended recursive least-squares (E-RLS) algorithms and reaches the conclusion that E-RLS is more feasible according to the comparison output of the simulation program from tracking performance and mean square error over five fast time variation of Rayleigh fading channels and more than one time (send/receive) reach to 100 times to make sure from efficiency of these algorithms.

A Genetic Algorithm optimization model is used in this study to find the optimum flow values of the Tigris river branches near Ammara city, which their water is to be used for central marshes restoration after mixing in Maissan River. These tributaries are Al-Areed, AlBittera and Al-Majar Al-Kabeer Rivers. The aim of this model is to enhance the water quality in Maissan River, hence provide acceptable water quality for marsh restoration. The model is applied for different water quality change scenarios ,i.e. , 10%,20% increase in EC,TDS and BOD. The model output are the optimum flow values for the three rivers while, the input data are monthly flows(1994-2011),monthly water requirements and water quality parameters (EC, TDS, BOD, DO and

In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

Target costing is one of the modern techniques in strategic Management accounting, Is has shown active adoption to changes in current business environments, In addition, is has seen a growth in strategic approach, The goal of using target costing is to build and strengthen competition abilities of economic units through introducing appropriate ways to decrease cost values while maintaining and improving quality of product, So this study is aim to show how can  economic units use target costing to achieve competitive advantages .

This paper presents an improved technique on Ant Colony Optimization (ACO) algorithm. The procedure is applied on Single Machine with Infinite Bus (SMIB) system with power system stabilizer (PSS) at three different loading regimes. The simulations are made by using MATLAB software. The results show that by using Improved Ant Colony Optimization (IACO) the system will give better performance with less number of iterations as it compared with a previous modification on ACO. In addition, the probability of selecting the arc depends on the best ant performance and the evaporation rate.

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

Bee keping projects is one of the most important agricltural investment projects because it generate profit in a short period . In addition to the multiplicity of products and other benefits . Research aimed at study the feasibility of two projects one hand in the origin of the Al – Mashrok since 2006 , kicking off with ten hives , and the scond proposal , kicking of 100 hives using the criteria of the world bank . Results showed that the bee keeping projects is economically feasible, whether small or large .. Even when the analysis of the sensitivity of the project to changes which may occur in the price of output and resources by reducing costs and increasing revenues by 10% it remains economically viable .