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Optimization of Thermal Aware VLSI Non-Slicing Floorplanning Using Hybrid Particle Swarm Optimization Algorithm-Harmony Search Algorithm
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作者 Sivaranjani Paramasivam Senthilkumar Athappan +1 位作者 Eswari Devi Natrajan Maheswaran Shanmugam 《Circuits and Systems》 2016年第5期562-573,共12页
Floorplanning is a prominent area in the Very Large-Scale Integrated (VLSI) circuit design automation, because it influences the performance, size, yield and reliability of the VLSI chips. It is the process of estimat... Floorplanning is a prominent area in the Very Large-Scale Integrated (VLSI) circuit design automation, because it influences the performance, size, yield and reliability of the VLSI chips. It is the process of estimating the positions and shapes of the modules. A high packing density, small feature size and high clock frequency make the Integrated Circuit (IC) to dissipate large amount of heat. So, in this paper, a methodology is presented to distribute the temperature of the module on the layout while simultaneously optimizing the total area and wirelength by using a hybrid Particle Swarm Optimization-Harmony Search (HPSOHS) algorithm. This hybrid algorithm employs diversification technique (PSO) to obtain global optima and intensification strategy (HS) to achieve the best solution at the local level and Modified Corner List algorithm (MCL) for floorplan representation. A thermal modelling tool called hotspot tool is integrated with the proposed algorithm to obtain the temperature at the block level. The proposed algorithm is illustrated using Microelectronics Centre of North Carolina (MCNC) benchmark circuits. The results obtained are compared with the solutions derived from other stochastic algorithms and the proposed algorithm provides better solution. 展开更多
关键词 VLSI Non-Slicing Floorplan Modified Corner List (MCL) algorithm hybrid particle swarm Optimization-Harmony Search algorithm (HPSOHS)
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Location layout design of aircraft parts assembly based on MSVR 被引量:6
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作者 Xining LI Zhihao ZHAO 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2020年第5期1532-1540,共9页
Location layout of aircraft assembly is an important factor affecting product quality.Most of the existing re-searches use the combination of finite element analysis and intelligent algorithm to optimize the location ... Location layout of aircraft assembly is an important factor affecting product quality.Most of the existing re-searches use the combination of finite element analysis and intelligent algorithm to optimize the location layout,which are limited by numerical simulation accuracy and the selection and improvement of intelligent algorithms.At present,the analysis and decision-making technology based on field data is gradually applied in aircraft manufacturing.Based on the perception data of intelligent assembly unit of aircraft parts,a regression model of multi-input and multioutput support vector machine with Gauss kernel function as radial basis function is established,and the hyperparameters of the model are optimized by hybrid particle swarm optimization genetic algorithm(PSO-GA).GA-MSVR,PSO-MSVR and PSOGA-MSVR model are constructed respectively,and their results show that PSOGA-MSVR model has the best performance.Finally,the design of the aircraft wing location layout is taken as an example to verify the effectiveness of the method. 展开更多
关键词 Aircraft parts ASSEMBLY hybrid particle swarm optimization genetic algorithm Location layout Multi-output support vector regression(MSVR) Perception data
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