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• W2605863669 abstract "Floorplanning is a crucial step in very large scale integration design flow. It provides valuable insights into the hardware decisions and estimates a floorplan with different cost metrics. In this paper, to handle a multi-objective thermal-aware non-slicing floorplanning optimization problem efficiently, an adaptive hybrid memetic algorithm is presented to optimize the area, the total wirelength, the maximum temperature and the average temperature of a chip. In the proposed algorithm, a genetic search algorithm is used as a global search method to explore the search space as much as possible, and a modified simulated annealing search algorithm is used as a local search method to exploit information in the search region. The global exploration and local exploitation are balanced by a death probability strategy. In this strategy, according to the natural mechanisms, each individual in the population is endowed with an actual age and a dynamic survival age. Experimental results on the standard tested benchmarks show that the proposed algorithm is efficient to obtain floorplans, with decreasing the average and the peak temperature." @default.
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• W2605863669 date "2017-06-01" @default.
• W2605863669 modified "2023-10-16" @default.
• W2605863669 title "An adaptive hybrid memetic algorithm for thermal-aware non-slicing VLSI floorplanning" @default.
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• W2605863669 doi "https://doi.org/10.1016/j.vlsi.2017.03.006" @default.
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