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Computational Social Choice is an interdisciplinary research area involving Economics, Political Science,and Social Science on the one side, and Mathematics and Computer Science(including Artificial Intelligence and Multiagent Systems) on the other side. Typical computational problems studied in this field include the vulnerability of voting procedures against attacks, or preference aggregation in multi-agent systems. Parameterized Algorithmics is a subfield of Theoretical Computer Science seeking to exploit meaningful problem-specific parameters in order to identify tractable special cases of in general computationally hard problems. In this paper, we propose nine of our favorite research challenges concerning the parameterized complexity of problems appearing in this context. This work is dedicated to Jianer Chen, one of the strongest problem solvers in the history of parameterized algorithmics,on the occasion of his 60 th birthday.  相似文献   

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将拟物方法与邻域搜索过程结合,得到求解不等圆Packing问题的拟物型邻域搜索算法(QP—NS).拟物方法用于连续优化,可从任一初始格局收敛至对应的局部最优格局;邻域搜索过程迭代地将当前格局替换为其邻域中的最优格局,直至无法继续改进当前格局为止.QP—NS可在不严重破坏当前格局的前提下稳定地改进当前格局,鲁棒性较强.基于14个国际公开算例的计算实验表明:QP-NS可在60S内改进10个算例的此前最优解,并与其余4个算例的此前最优解持平.  相似文献   

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平面图形的最小覆盖圆问题是一类有趣且具有适用价值的问题,在中考中时有所见,现举两例与同学们共同探求其解题方法.例1(2008年连云港)我们将能完全覆盖某平面图形的最小圆称为该平面图形的最小覆盖圆.例如线段AB的最小覆盖圆就是以线段AB为直径的圆.  相似文献   

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