Factors affecting the tendency to leave the organization using an intelligent model based on multi-objective neural network and genetic algorithms

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Khaziri Afravi Saham; SARDARI ZARCHI MOHSEN; FATEMI BUSHEHRI SEYED MOHAMMAD MEHDI

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Journal: مطالعات راهبردی در صنعت نفت و انرژی Year:2019 | Volume:10 | Issue:38 Page(s): 75-104

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Title

Factors affecting the tendency to leave the organization using an intelligent model based on multi-objective neural network and genetic algorithms

Author(s)

Khaziri Afravi Saham | SARDARI ZARCHI MOHSEN | FATEMI BUSHEHRI SEYED MOHAMMAD MEHDI | Issue Writer Certificate

Keywords

ReplacementQ1

Data MiningQ1

SelectionQ1

Artificial Neural NetworkQ2

Multi-Objective Genetic AlgorithmQ2

Abstract

Since the improvement of human resource efficiency can play an effective role in the efficiency of organizations, it has always been one of the main research topics. The tendency to leave the organization is one of the factors affecting the efficiency of human capital, which can be predicted using in-data models, conditions governing the organization and the factors affecting it. For this purpose, intelligent algorithms based on neural network and Multi-Objective Genetic Algorithm have been used in this research to predict the tendency to leave an organization. In this regard, a standard dataset was created based on a questionnaire of employees satisfaction and the desire to leave the job in the Karoon Oil and Gas Production Company. Then, using an Artificial Neural Network as a classifier and a Multi-Objective Genetic Algorithm, the important factors or features were selected. In the next step, an expert system was proposed to select effective features. In order to test and evaluate the neural network algorithm developed with the standard data set, the necessary training was provided. The results showed that by using the proposed model, not only the willingness of employees to leave the organization can be predicted with more than 88% accuracy, but also, the key factors of leaving the organization can be determined.

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APA: Copy

Khaziri Afravi, Saham, SARDARI ZARCHI, MOHSEN, & FATEMI BUSHEHRI, SEYED MOHAMMAD MEHDI. (2019). Factors affecting the tendency to leave the organization using an intelligent model based on multi-objective neural network and genetic algorithms. STRATEGIC STUDIES IN PETROLEUM AND ENERGY INDUSTRY (HUMAN RESOURCE MANAGEMENT IN THE OIL INDUSTRY), 10(38 ), 75-104. SID. https://sid.ir/paper/196612/en

Vancouver: Copy

Khaziri Afravi Saham, SARDARI ZARCHI MOHSEN, FATEMI BUSHEHRI SEYED MOHAMMAD MEHDI. Factors affecting the tendency to leave the organization using an intelligent model based on multi-objective neural network and genetic algorithms. STRATEGIC STUDIES IN PETROLEUM AND ENERGY INDUSTRY (HUMAN RESOURCE MANAGEMENT IN THE OIL INDUSTRY)[Internet]. 2019;10(38 ):75-104. Available from: https://sid.ir/paper/196612/en

IEEE: Copy

Saham Khaziri Afravi, MOHSEN SARDARI ZARCHI, and SEYED MOHAMMAD MEHDI FATEMI BUSHEHRI, “Factors affecting the tendency to leave the organization using an intelligent model based on multi-objective neural network and genetic algorithms,” STRATEGIC STUDIES IN PETROLEUM AND ENERGY INDUSTRY (HUMAN RESOURCE MANAGEMENT IN THE OIL INDUSTRY), vol. 10, no. 38 , pp. 75–104, 2019, [Online]. Available: https://sid.ir/paper/196612/en

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