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

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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.

Creativity matrix
Intelligent clustering
Cubic space clustering
Genetic algorithm
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