Abstract
Machine learning and linear programming with time dependent cost are two popular intelligent optimization tools to handle uncertainty in real world problems. Thus, combining these two technologies is quite attractive. This paper proposed an effective framework to deal with uncertainty in practice, based on combing introducing learning parameter into linear programming models.
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