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Multi-objectives probabilistic Aggregate production planning with practical application
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In this research, has been to building a multi objective Stochastic Aggregate Production Planning model for General al Mansour company Data with Stochastic  demand under changing of market and uncertainty environment in aim to draw strong production plans.  The analysis to derive insights on management issues regular and extra labour costs and the costs of maintaining inventories and good policy choice under the influence medium and optimistic adoption of the model of random has adoption form and had adopted two objective functions total cost function (the core) and income and function for a random template priority compared with fixed forms with objective function and the results showed that the model of two phases with  k = 4 is the best model of random which contributed to reducing costs by approximately 7%. It was also a statement that the change in the total costs will be changed by the possibilities associated with cases predicted demand (scenarios) where we note the low cost and with a high probability of low demand. In contrast, the total cost increases with increasing demand. Because the change in the possibilities leads to change in the Production plan for future. As well as the building and solving model multi-objectives by constraint method improved (augmented) and the results were derived a set of acceptable solutions rather than a single solution and thus can be a decision-maker to choose the best solution for the specific case of the optimization problem of multiple objectives, was Form solution using the developed software GAMS

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Publication Date
Mon Jun 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Evaluation of performance of some industrial companies In the default reference comparison method Field study in the public companies of cement (Iraqi - North - South
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The increasing Global Competitive and the continuous improvement in information technology has led the way to the development of the modern systems and using modern techniques. One of these techniques is benchmarking style and Total Quality Management all of them are used to improve the production process and target rid from the losts on the other side.

The Benchmarking style has become a very important for all the industrial systems and the serving systems as well. And an instrument to improve their performance specially those which are suffering from the highness of the costs or waste in time on the other side.

This study aims to depend on virtual Benchmarking style in the eval

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Comparison for estimation methods for the autoregressive approximations
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Abstract

      In this study, we compare between the autoregressive approximations (Yule-Walker equations, Least Squares , Least Squares ( forward- backword ) and Burg’s (Geometric and Harmonic ) methods, to determine the optimal approximation to the time series generated from the first - order moving Average non-invertible process, and fractionally - integrated noise process, with several values for d (d=0.15,0.25,0.35,0.45) for different sample sizes (small,median,large)for two processes . We depend on figure of merit function which proposed by author Shibata in 1980, to determine the theoretical optimal order according to min

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