An alternative for decreasing risk for knowledge workers is effective & optimized work break.Major performance criteria in R&D based organization is successful projects. Selection of opproporiate members can be a most effect on the projects achievement. But as the selection of R&D special members lead to decrease of risk, repeatative participation of this people in the same project lead to knowledge concentration and achieve organization with serios risks. Therefore attendance to knowledge and quality project angles is important to selection of R&D teams members. In this study, we developed a model based on Non-Dominated Sorting Genetic Algorithm.
Nikookar, G., Alidadi Nakhlestani, Y., Mahdavi, M., & Mousavi, S. J. (2014). Non-Dominated Sorting Genetic Algorithm to inegrated model for R&D members selection. Industrial Management Journal, 6(2), 385-410. doi: 10.22059/imj.2014.51848
MLA
Gholamhossein Nikookar; Yaser Alidadi Nakhlestani; Mohammad Mahdavi; Seyed Jalal Mousavi. "Non-Dominated Sorting Genetic Algorithm to inegrated model for R&D members selection", Industrial Management Journal, 6, 2, 2014, 385-410. doi: 10.22059/imj.2014.51848
HARVARD
Nikookar, G., Alidadi Nakhlestani, Y., Mahdavi, M., Mousavi, S. J. (2014). 'Non-Dominated Sorting Genetic Algorithm to inegrated model for R&D members selection', Industrial Management Journal, 6(2), pp. 385-410. doi: 10.22059/imj.2014.51848
VANCOUVER
Nikookar, G., Alidadi Nakhlestani, Y., Mahdavi, M., Mousavi, S. J. Non-Dominated Sorting Genetic Algorithm to inegrated model for R&D members selection. Industrial Management Journal, 2014; 6(2): 385-410. doi: 10.22059/imj.2014.51848
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