THE ROLE OF WOMEN IN ENVIRONMENTAL PROTECTION IN IGABI LOCAL GOVERNMENT, KADUNA STATE, NIGERIA
Hypothesis 2: Ineffective Utilization of Resources has no impact on sub-optimality in production in
4. Empirical results
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element in a particular vector. If the element is a one it is mutated to zero, and viceversa. This occurs with a very low probability in order not to destroy promising areas of search space.
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Notes: GMA trading rules are identified as (s,l,b), where s and l are the length of the short and long period (in days) and b is the filter parameter.
is the average annualized return of the trading strategy and SR is the Sharpe ratio .
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Assess and Identify Factors Associated With Improved Information Systems For Performance Assessment Production Methodology Push Versus Pull Systems (Case Study
of Electronic Industries of Iran)
Shahram Gilaninia (Corresponding Author)
Assistant professor , Department of management, invited professor in Astara Branch, Islamic Azad University, Astara, Iran
Seyyed Javad Mousavian
Master of Islamic Azad university , Department of management, invited master in Astara Branch, Islamic Azad University, Astara, Iran
Musa Rezvani
Faculty Member ,Department of management, Astara Branch, Islamic Azad University, Astara, Iran
Abstract
This paper first researcher to introduce short of push and pull systems is then paid to the effect of various factors related to information systems are and can evaluate performance of many organizations to help study the research has In the present part of E Company was undertaken by using appropriate statistical methods and indicators that were identified.
Keywords: Performance, DSS, indicators, assessment.push production 1.Introduction
managers contemplating the installation of a pull system cannot measure progress toward meeting pull system goals without knowing the significant metrics of his system. This manager also requires a method for predicting when the system should change from one transition state to the next and a means to control the analysis of these changing metrics. The methods presented fulfill these needs. First, a simulation model of a real electronics assembly system is developed.
The simulation model provides a case study, a mechanism for obtaining data and a vehicle for method validation. Step-wise multiple regression is used to determine which factors and factor interactions significantly influence the simulation model output. The transition functions of pull system implementation are then estimated using dynamic programming. Validation of the transition functions is accomplished by comparing simulated results and results predicted by using the transition functions. A decision support system framework provides guidelines for the development of software employing these methods.