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兰州理工大学 [6]

西安交通大学 [2]

厦门大学 [1]

电工研究所 [1]

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山东大学 [1]

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	Research on application of a type of improved simulated annealing algorithm for the transit vehicle scheduling 期刊论文 Journal of Information and Computational Science, 2014, 卷号: 11, 期号: 3, 页码: 867-874 作者: Wang, Qingrong 收藏 \| 浏览/下载：16/0 \| 提交时间：2020/11/14 Genetic algorithms Stochastic models Complicated systems Improved simulated annealing algorithm Nested partitions Optimization modeling SA Simulated annealing algorithms Stochastic combinatorial optimization Transit vehicles
	基于遗传和模拟退火算法求解3-SAT问题期刊论文 2012 饶丽丽; 张东站收藏 \| 浏览/下载：3/0 \| 提交时间：2016/05/17 SAT Johnson算法遗传算法模拟退火算法 SAT Johnson Algorithm Genetic Algorithm Simulated Annealing Algorithm
	Hybrid evolutionary algorithms in a SVR traffic flow forecasting model 期刊论文 APPLIED MATHEMATICS AND COMPUTATION, 2011, 卷号: 217, 期号: [db:dc_citation_issue], 页码: 6733-6747 作者: Hong, Wei-Chiang; Dong, Yucheng; Zheng, Feifeng; Wei, Shih Yung 收藏 \| 浏览/下载：9/0 \| 提交时间：2019/12/10 Traffic flow forecasting Holt-Winters (HW) Support vector regression Hybrid genetic algorithm-simulated annealing algorithm (GA-SA) SARIMA Back-propagation neural network BPNN Hybrid evolutionary algorithms Seasonal Holt-Winters (SHW)
	A robust adaptive hybrid genetic simulated annealing algorithm for the global optimization of multimodal functions 会议论文作者: Xu, Qiaoling; Zhang, Gongwang; Zhao, Chao; An, Aimin 收藏 \| 浏览/下载：2/0 \| 提交时间：2020/11/15 Global optimization Iterative methods Local search (optimization) Simulated annealing Adaptive scheme Complex optimization problems Genetic simulated annealing Genetic simulated annealing algorithms Global searching ability Hill climbing Hybrid genetic algorithms Local search techniques
	A Robust Adaptive Hybrid Genetic Simulated Annealing Algorithm for the global optimization of multimodal functions 会议论文作者: Xu, Qiaoling; Zhang, Gongwang; Zhao, Chao; An, Aimin 收藏 \| 浏览/下载：0/0 \| 提交时间：2019/11/15 genetic simulated annealing iterative hill climbing (IHC) method adaptive scheme global optimization
	Taiwanese 3G mobile phone demand forecasting by SVR with hybrid evolutionary algorithms 期刊论文 EXPERT SYSTEMS WITH APPLICATIONS, 2010, 卷号: 37, 期号: 6, 页码: 4452-4462 作者: Hong, Wei-Chiang; Dong, Yucheng; Chen, Li-Yueh; Lai, Chien-Yuan 收藏 \| 浏览/下载：6/0 \| 提交时间：2019/12/18 General regression neural networks (GRNN) Demand forecasting Autoregressive integrated moving average (ARIMA) Support vector regression (SVR) Third generation (3G) mobile phone Genetic algorithm-simulated annealing (GA-SA)
	Parallel adaptive hybrid genetic optimization algorithm and its application 会议论文 Wuhan, China, November 28, 2009 - November 29, 2009 作者: An, Aimin; Hao, Xiaohong; Yuan, Guici; Zhao, Chao; Su, Hongye 收藏 \| 浏览/下载：1/0 \| 提交时间：2020/11/15 Artificial intelligence Genetic algorithms Simulated annealing Genetic simulated annealing Genetic simulated annealing algorithms Global searching ability Heat-exchange networks Hill climbing Hybrid genetic algorithms Hybrid mechanisms Simulated annealing algorithms
	GSA-based maximum likelihood estimation for threshold vector error correction model 期刊论文 COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2007, 卷号: 52, 期号: 1, 页码: 109-120 作者: Yang, Zheng; Tian, Zheng; Yuan, Zixia 收藏 \| 浏览/下载：17/0 \| 提交时间：2015/11/08 threshold vector error correction model maximum likelihood estimation genetic-simulated annealing
	A PSO and Simulated Annealing Hybrid Algorithm to task allocation problem for holonic manufacturing system 会议论文作者: Yang, Yahong; Zhao, Fuqing; Yao, Yunping; Zhu, Aihong 收藏 \| 浏览/下载：5/0 \| 提交时间：2019/11/15 holonic manufacturing control dynamic clustering particle swarm optimization genetic algorithm optimum control
	A PSO and simulated annealing hybrid algorithm to task allocation problem for holonic manufacturing system 会议论文 Dalian, China, June 21, 2006 - June 23, 2006 作者: Yang, Yahong; Zhao, Fuqing; Yao, Yunping; Zhu, Aihong 收藏 \| 浏览/下载：0/0 \| 提交时间：2020/11/15 Genetic algorithms Global optimization Probability Production control Simulated annealing Dynamic clustering Holonic manufacturing control Holonic manufacturing systems (HMS) Optimum control Particle swarm optimization Task allocation

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