摘要翻译：
本文提出了一个新的布局优化问题的算法，该问题涉及在圆形容器内放置加权多边形，其两个目标是使质量不平衡最小化和使容器半径最小化。这一问题在工业应用（如卫星设计）中具有实际意义，也具有重要的理论意义。以前的工作已经处理了圆形或矩形物体，但这里我们处理了更现实的情况，即物体可以表示为多边形，并且允许多边形旋转。提出了一种基于模拟退火算法的解决方案，并在已知最优解的实例上进行了测试。结果表明，该算法可以得到接近最优的容器半径。对于特殊的矩形情况，我们还将我们的方法与现有的算法进行了比较。实验结果表明，在解的质量方面，我们的方法优于这些方法。
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英文标题：
《Simulated annealing for weighted polygon packing》
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作者：
Yi-Chun Xu, Ren-Bin Xiao and Martyn Amos
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最新提交年份：
2008
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Computational Geometry        计算几何
分类描述：Roughly includes material in ACM Subject Classes I.3.5 and F.2.2.
大致包括ACM课程I.3.5和F.2.2中的材料。
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一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  In this paper we present a new algorithm for a layout optimization problem: this concerns the placement of weighted polygons inside a circular container, the two objectives being to minimize imbalance of mass and to minimize the radius of the container. This problem carries real practical significance in industrial applications (such as the design of satellites), as well as being of significant theoretical interest. Previous work has dealt with circular or rectangular objects, but here we deal with the more realistic case where objects may be represented as polygons and the polygons are allowed to rotate. We present a solution based on simulated annealing and first test it on instances with known optima. Our results show that the algorithm obtains container radii that are close to optimal. We also compare our method with existing algorithms for the (special) rectangular case. Experimental results show that our approach out-performs these methods in terms of solution quality.
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PDF链接：
https://arxiv.org/pdf/0809.5005