Hybrid Architecture of Genetic Algorithm and Simulated Annealing
Hybrid Architecture of Genetic Algorithm and Simulated Annealing
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发表时间：
2008
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通讯作者：
M. Yoshikawa;Hironori Yamauchi;H. Terai
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作者：
M. Yoshikawa;Hironori Yamauchi;H. Terai
本文讨论了基于遗传算法（GA）和模拟退火（SA）的混合优化的新型专用硬件架构。所提出的架构实现了高速处理。而且，它不仅实现了全局搜索，还实现了局部搜索。为了保持通用性，引入了握手系统的自控处理。通过采用握手系统，所提出的架构可以仅通过改变编码器、解码器和评估电路来应用于各种组合优化问题。此外，所提出的架构实现了遗传算法上许多遗传操作的灵活性。为了评估所提出的架构，我们进行了两种实验。一个是将所提出的架构应用于 TSP 的实验，另一个是将其应用于 VLSI 布局规划的实验。这些实验结果证明所提出的架构实现了高速处理，同时保持了解决方案的质量。
This paper discusses novel dedicated hardware architecture for hybrid optimization based on Genetic algorithm (GA) and Simulated Annealing (SA). The proposed architecture achieves high speed processing. Moreover, it achieves the searching not only globally, but also locally. To keep general purpose, self-control processing by a handshake system is introduced. By adopting the handshake system, the proposed architecture can be applied to various combinatorial optimization problems by only changing an encoder, a decoder, and an evaluation circuit. Furthermore, the proposed architecture realizes flexibility for many genetic operations on GA. In order to evaluate the proposed architecture, we conduct two kinds of experiments. One is an experiment which applies the proposed architecture to TSP, and the other is an experiment which applies it to VLSI floorplanning. These experiment results prove that the proposed architecture achieves high speed processing, while keeping the quality of the solutions.