A genetic algorithm for a creativity matrix cubic space clustering: A case study in Mazandaran Gas Company

Authors:
Amin Aalaei;Hamed Fazlollahtabar;Iraj Mahdavi;Nezam Mahdavi-Amiri;Mohammad Hassan Yahyanejad
Affiliations:
Department of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran;Faculty of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran;Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran;Faculty of Mathematical Sciences, Sharif University of Technology, Tehran, Iran;Mazandaran Gas Company, Sari, Iran
Venue:
Applied Soft Computing
Year:
2013

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Abstract

Creativity is a promoting factor in organizations. Having employees in structured and organized configurations in a creative manner, helps in improving the productivity. We investigate different structural aspects of teams' network organization and the creativity within a knowledge development program (KDP). The proposed methodology being equipped with a heuristic clustering technique, classifies the employees with respect to creativity parameters and configures a creativity matrix. Applying the creativity matrix, clustering is performed via mathematical programming. For large problems, a genetic algorithm (GA) is developed to solve the mathematical model. We also employ the Taguchi method to evaluate the effects of different operators and parameters on the performance of GA. A case study conducted in Mazandaran Gas Company in Iran illustrates the applicability and effectiveness of the proposed methodology.