计算机应用与软件2026，Vol.43Issue(5)：170-176,7.DOI:10.3969/j.issn.1000-386x.2026.05.023
基于循环强化学习和模拟退火的布图规划算法
FLOORPLAN ALGORITHM BASED ON CYCLIC REINFORCEMENT LEARNING AND SIMULATED ANNEALING
摘要
Abstract
Electronic design automation(EDA)involves a series of computationally difficult optimization problems,among which floorplan optimization is a critical step in chip design.Recently,reinforcement learning(RL)-based methods have been successfully applied to deal with various combinatorial optimization problems.For the floorplan problem,a floorplan algorithm based on reinforcement learning(RL)and simulated annealing(SA)is proposed.This algorithm constructed an RL-SA loop framework,adopted sequence pair(SP)to represent floorplan structure,and utilized the ability of RL models to quickly obtain good rough solutions after training and the ability of heuristic algorithms to implement greedy improvement in solutions to obtain good floorplan.Experimental results show that RL can provide SA with a good initial floorplan,thereby generating better floorplan designs.关键词
布图规划/强化学习/模拟退火/序列对Key words
Floorplan/Reinforcement learning/Simulated annealing/Sequence pair分类
信息技术与安全科学引用本文复制引用
余胜录,杜世民..基于循环强化学习和模拟退火的布图规划算法[J].计算机应用与软件,2026,43(5):170-176,7.基金项目
国家自然科学基金项目(61871244,61874078) （61871244,61874078）
浙江省高校科研项目(SJLY2020015). （SJLY2020015）
