VLSI elements placement based on simulation of bats behavior in nature

E. Kuliev, A. Lezhebokov, Y. Kravchenko
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Abstract

The paper deals with NP-hard optimization problems with the use of behavioral foundations of subject in nature. Swarm intelligent methods and algorithms are the most promising ones. Suggested algorithm is based on the simulation of bats' behavior. The authors concern a behavioral model of a bat — it moves within search space for the purpose of finding quasi-optimal solutions. Also there are represented approaches to adjust control parameters of the algorithm (frequency, amplitude, direction of movement). On the basis of bat's behavior a schematic diagram is developed. Initial search space are formed by sequential, random and iterative algorithms. To confirm theoretical estimations of time complexity and effectiveness of the developed algorithm computational experiments are carried out.
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基于蝙蝠在自然界行为模拟的VLSI元件放置
本文利用自然界主体的行为基础来研究NP-hard优化问题。群智能方法和算法是最有前途的。提出的算法是基于对蝙蝠行为的模拟。作者关注蝙蝠的行为模型——它在搜索空间内移动以寻找准最优解。此外,还有调整算法控制参数(频率、幅度、运动方向)的代表性方法。在分析蝙蝠行为的基础上,提出了蝙蝠行为的原理图。初始搜索空间由顺序、随机和迭代算法组成。为了验证理论估计的时间复杂度和所开发算法的有效性,进行了计算实验。
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