Courses timetabling based on hill climbing algorithm
نویسندگان
چکیده
منابع مشابه
When a genetic algorithm outperforms hill-climbing
A toy optimisation problem is introduced which consists of a ÿtness gradient broken up by a series of hurdles. The performance of a hill-climber and a stochastic hill-climber are computed. These are compared with the empirically observed performance of a genetic algorithm (GA) with and without. The hill-climber with a suuciently large neighbourhood outperforms the stochastic hill-climber, but i...
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Many learning systems search through a space of possible performance elements, seeking an element whose expected utility, over the distribution of problems, is high. As the task of nding the globally optimal element is often intractable, many practical learning systems instead hill-climb to a local optimum. Unfortunately, even this is problematic as the learner typically does not know the under...
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For a given classification task, there are typically several learning algorithms available. The question then arises: which is the most appropriate algorithm to apply. We recently proposed a new algorithm for making such a selection based on landmarking a recent meta-learning strategy that utilises meta-features that are themselves efficient learning algorithms. This algorithm, which creates a ...
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Many learning tasks involve searching through a discrete space of performance elements, seeking an element whose future utility is expected to be high. As the task of nding the global optimum is often intractable, many practical learning systems use simple forms of hill-climbing to nd a locally optimal element. However, hill-climbing can be complicated by the fact that the utility value of a pe...
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ژورنال
عنوان ژورنال: International Journal of Electrical and Computer Engineering (IJECE)
سال: 2020
ISSN: 2722-2578,2088-8708
DOI: 10.11591/ijece.v10i6.pp6558-6573