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Solving Multicriteria University Timetabling Problem by a Self-adaptive Genetic Algorithm with Minimal Perturbation

机译:用最小扰动的自适应遗传算法解决多准则大学排课问题

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摘要

The most of methods for solving the university timetabling problem deal with the problem statically, which makes great difficulties when requirements are changed, because a new timetable is usually very different from the previous one. To overcome it the minimal perturbation problem is incorporated into the timetabling model. For solving the model a self-adaptive genetic algorithm was proposed. Comparing to previous approaches we designed the encoding for self-adaptation not only one parameter or several ones but for all possible parameters of genetic algorithms at the same time. Also the multicriteria system for timetable evaluation is presented.
机译:解决大学时间表问题的大多数方法都是静态地解决该问题,因此在更改需求时会遇到很大的困难,因为新时间表通常与前一个时间表大不相同。为了克服它,最小扰动问题被合并到时间表模型中。为了求解该模型,提出了一种自适应遗传算法。与以前的方法相比,我们设计了针对自适应的编码,不仅可以自适应一个参数或多个参数,而且还可以同时针对遗传算法的所有可能参数进行自适应。还介绍了时间表评估的多准则系统。

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