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Fazlollahtabar H.,Iran University of Science and Technology | Hassanzadeh R.,Allameh Mohaddes Noori Institute | Mahdavi I.,Mazandaran University of Science and Technology | Mahdavi-Amiri N.,Sharif University of Technology
Journal of the Chinese Institute of Industrial Engineers | Year: 2012

This work considers scheduling problems minding the setup and removal times of jobs rather than processing times. For some production systems, setup times and removal times are so important to be considered independent of processing times. In general, jobs are performed according to the automatic machine processing in production systems, and the processing times are considered to be constant regardless of the process sequence. As the human factor can influence the setup and removal times, when the setup process is repetitive the setup times decreases. This fact is considered as learning effect in scheduling literature. In this study, a bi-criteria m-identical parallel machines scheduling problem with learning effects of setup and removal times is considered. The learning effect is proposed using a perceptron neural network algorithm. The objective function of the problem is minimization of the weighted sum of total earliness and tardiness. A mathematical programming model is developed for the problem, which is NP-hard. Results of computational tests show that the LINGO 9 software is effective in solving problems with up to 25 jobs and five machines. Therefore, for larger sized problems, a genetic algorithm for optimization is developed. © 2012 Chinese Institute of Industrial Engineers.


Farkhondeh H.,Mazandaran University of Science and Technology | Hassanzadeh R.,Allameh Mohaddes Noori Institute | Mahdavi I.,Mazandaran University of Science and Technology | Mahdavi-Amiri N.,Sharif University of Technology
International Journal of Advanced Manufacturing Technology | Year: 2012

Line balancing problem plays an important role in the decision making process to increase efficiency and productivity. Recently, U-shaped layout in many production lines has replaced the traditional straight line layout using just-in-time concept. Here, we propose a model, using multi-objective decision making approach to the U-shaped line balancing problem, to offer enhanced decision maker flexibility, by allowing for conflicting goals. The assembly line operation efficiency is the most significant aim in our study, and this efficiency relates to management of resources and the solution of line balancing problem. First, the U-shaped line balancing problem is solved considering the model's goals. Then, the index function of assembly line balancing is determined and the efficiencies of the optimal solution outputs are evaluated using data envelopment analysis (DEA). Finally, the discrimination weakness and distribution of illogical weight in simple DEA models are resolved using a mixed method. © 2011 Springer-Verlag London Limited.

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