Using Fuzzy Cognitive Maps for Prediction of Knowledge Worker Productivity Based on Real Coded Genetic Algorithm

Authors

Abbas Afrazeh Assistant professor Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran

Asadallah Najafi Department of Engineering and Technology, Islamic Azad University, Zanjan Branch, Zanjan, Iran

Abstract:

Improving knowledge worker productivity has been one of the most important tasks of the century. However, we have few measures or management interventions to make such improvement possible, and it is difficult to identify patterns that should be followed by knowledge workers because systems and processes in an organization are often regarded as a death blow to creativity. In this paper, we seek to present a method for prediction of Knowledge worker productivity (KWP) that it must be capable of predicting the productivity of the knowledge workers in a one year period of time based on the Fuzzy cognitive maps (FCM) technique Based on Real Coded Genetic Algorithm (RCGA) , as well as presenting the best option from among different options as the knowledge workers’ productivity improving strategy (suggesting solution), based on the results gained from this and the previous section and depending on the requirements. The validity of the suggested model will be tested in an Iranian Company .

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Journal title

International Journal of Industrial Engineering and Productional Research-

volume 22 issue 1

pages 21- 30

publication date 2011-03

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