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Using a Social Media Inspired Optimization Algorithm to Solve the Set Covering Problem

机译:使用社交媒体启发优化算法来解决集合涵盖问题

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Currently, researchers have focused on solving large-scale and non-linear optimization problems. Metaheuristics as its prefix indicates, are superior heuristics that aim to deliver acceptable results to optimization problems in a short period of time, trying to achieve a correct balance between exploration and exploitation in the search for solutions. In this paper we present the application of a metaheuristic technique called Social media optimization algorithm for the resolution of the Set Covering Problem (SCP). This technique is inspired by the behavior of users of social networking platforms such as Twitter. The users through different interactions manage to make a Tweet more relevant than others. The user who generates the best Tweet, is recognized as a celebrity. This process of social relationship is precisely what allows us to find better solutions given the experiments and results presented in this document.
机译:目前,研究人员专注于解决大规模和非线性优化问题。常见问题是其前缀表示,旨在在短时间内提供可接受的结果,以在短时间内提供可接受的结果,试图在寻求解决方案中实现勘探和利用之间的正确平衡。在本文中,我们介绍了一种常规技术的应用,称为社交媒体优化算法以解决集合覆盖问题(SCP)。这种技术受到诸如Twitter等社交网络平台的用户的行为的启发。通过不同的交互用户可以管理比其他交往更相关。生成最佳推文的用户被认为是名人。鉴于本文件中提出的实验和结果,这一社会关系的过程正是允许我们找到更好的解决方案。

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