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A knowledge-based heuristic particle swarm optimization approach with the adjustment strategy for the weighted circle packing problem

机译:基于知识的启发式粒子群优化方法及加权圆堆积问题的调整策略

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摘要

The weighted circle packing problem is a kind of important combination optimization problem and has the NP-hard property. Inspired by the No Free Lunch Theorem, a knowledge-based heuristic particle swarm optimization approach with the adjustment strategy (KHPSOA) is developed for this problem. The knowledge (e.g., the relation between its weight matrix and better solution) is obtained from this problem itself and existing layout scheme diagrams and applied to form more effective ordering and positioning rules of the proposed heuristic method. A better layout scheme of larger circles is obtained through the heuristic method. The optimal solution of this problem is obtained by inserting a few residual smaller circles into the gaps of the better layout scheme and further optimizing it through the proposed particle swarm optimization with the adjustment strategy. The numerical experiments show that KHPSOA is superior to the existing algorithms in the performances.
机译:加权圆堆积问题是一种重要的组合优化问题,具有NP-hard属性。受“免费午餐定理”的启发,针对此问题开发了一种基于知识的启发式粒子群优化方法,并带有调整策略(KHPSOA)。从该问题本身和现有的布局方案图获得知识(例如其权重矩阵与更好的解决方案之间的关系),并将其应用于形成所提出的启发式方法的更有效的排序和定位规则。通过启发式方法可以获得较大的圆的更好的布局方案。通过将一些剩余的较小的圆插入到更好的布局方案的间隙中,然后通过提出的带有调整策略的粒子群优化算法对其进行优化,可以获得该问题的最佳解决方案。数值实验表明,KHPSOA在性能上优于现有算法。

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