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- 采用遗传算法和模拟退火算法解决ＶＬＳＩ中的布局优化问题
daima
- 遗传-模拟退火算法解决组合优化问题，结合遗传算法与模拟退火算法各自的优点-Genetic- simulated annealing algorithm to solve combinatorial optimization problems, the respective advantages of the combination of genetic algorithms and simulated annealing algorithm
09021425
- 聚类算法，以及基于遗传模拟退火算法的聚类算法，优化聚类算法-Clustering algorithm, and the clustering algorithm based on genetic simulated annealing algorithm to optimize the clustering algorithm
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- 基于混沌粒子群与模拟退火优化算法的最小二乘支持向量机参数自选择方法-Based on Chaotic Particle Swarm Optimization Algorithm and Simulated Annealing least squares support vector machine parameters from selection method
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- 基于混沌粒子群与模拟退火优化算法的最小二乘支持向量机参数自选择方法-Based on Chaotic Particle Swarm Optimization Algorithm and Simulated Annealing least squares support vector machine parameters from selection method
simulated-annealing
- 智能优化算法—模拟退火算法解旅行商路径最短-Intelligent optimization algorithm- simulated annealing algorithm for solving the traveling salesman shortest path
遗传模拟退火
- 遗传模拟退火算法，包括遗传算法及加入退火优化，退火算法可以跳出局部最优解。