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A Hybrid Algorithm Combining an Evolutionary Algorithm and a Simulated Annealing Algorithm to Solve a Collaborative Learning Team Building Problem

机译:融合进化算法和模拟退火算法的混合算法解决协作学习团队建设问题

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In this paper, we address a collaborative learning team building problem that considers a grouping criterion successfully analyzed in the context of software engineering courses. This criterion is based on taking into account the team roles of the students and on building well-balanced teams according to the team roles of their members. To solve the problem, we propose a hybrid algorithm. This algorithm incorporates a simulated annealing algorithm into the framework of an evolutionary algorithm with the aim of improving the performance of the evolutionary search. The simulated annealing algorithm adapts its behavior according to the evolutionary search state. The performance of the hybrid algorithm on ten data sets is compared with those of the algorithms previously proposed in the literature for solving the addressed problem. The obtained results show that the hybrid algorithm significantly outperforms the previous algorithms.
机译:在本文中,我们解决了一个协作学习团队建设问题,该问题考虑了在软件工程课程中成功分析的分组标准。此标准基于考虑到学生的团队角色,并根据其成员的团队角色建立均衡的团队。为了解决这个问题,我们提出了一种混合算法。该算法将模拟退火算法结合到进化算法的框架中,旨在提高进化搜索的性能。模拟退火算法根据进化搜索状态调整其行为。将混合算法在十个数据集上的性能与文献中先前提出的用于解决该问题的算法的性能进行比较。获得的结果表明,混合算法明显优于以前的算法。

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