Using Fuzzy Cognitive Maps for Prediction of Knowledge Worker Productivity Based on Real Coded Genetic Algorithm
Publish place: International Journal of Industrial Engineering & Production Research، Vol: 22، Issue: 1
Publish Year: 1390
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_IJIEPR-22-1_003
تاریخ نمایه سازی: 7 شهریور 1393
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 Fuzzycognitive 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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Authors
Asadallah Najafi
Department of Engineering and Technology, Islamic Azad University, Zanjan Branch, Zanjan, Iran
Abbas Afrazeh
Assistant professor Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran