1
Assistant Professor, Shahid Beheshti University.
2
Associate Professor, Shahid Beheshti University.
3
Professor, Shahid Beheshti University.
Abstract
Seeing that a lean cell performance is directly related to assigned operators, this article incorporates boredom in term of continually repeating working cycles as a function of the way in which operators assigned to and rotated in the cell during a specified short-term horizon and develops an integer nonlinear model to two problems, namely balancing and assignment in the case of arranging a new cell. The model is to satisfy some goals in term of lean performance measures and classic ones. None of the optimization packages is able to solve even the small size samples of the model due to formulating great number of nonlinear inequalities and non-pre-identified number of work cycles for each assigned operator per each rotation interval, as well. So, by applying the benefits of genetic algorithm the model is solved.
Ayough, A., Zandieh, M., Farsijani, H., & Dorri Nokarani, B. (2014). Job Rotation Scheduling in a New Arranged Lean Cell, a Genetic Algorithm Approach. Journal of Industrial Management Perspective, 4(3), 33-59.
MLA
Ashkan Ayough; Mostafa Zandieh; Hassan Farsijani; Behrooz Dorri Nokarani. "Job Rotation Scheduling in a New Arranged Lean Cell, a Genetic Algorithm Approach", Journal of Industrial Management Perspective, 4, 3, 2014, 33-59.
HARVARD
Ayough, A., Zandieh, M., Farsijani, H., Dorri Nokarani, B. (2014). 'Job Rotation Scheduling in a New Arranged Lean Cell, a Genetic Algorithm Approach', Journal of Industrial Management Perspective, 4(3), pp. 33-59.
VANCOUVER
Ayough, A., Zandieh, M., Farsijani, H., Dorri Nokarani, B. Job Rotation Scheduling in a New Arranged Lean Cell, a Genetic Algorithm Approach. Journal of Industrial Management Perspective, 2014; 4(3): 33-59.
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