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沈阳自动化研究所 [9]

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	Differential evolution algorithm with dynamic multi-population applied to flexible job shop schedule 期刊论文 Engineering Optimization, 2022, 卷号: 54, 期号: 3, 页码: 387-408 作者: Cao Y(曹阳); Shi HB(史海波); Chang DL(常大亮) 收藏 \| 浏览/下载：12/0 \| 提交时间：2021/03/14 Flexible job shop scheduling problem differential evolution algorithm multi-objective optimization multiple subpopulations strategy adaptation
	Adaptive population NSGA-III with dual control strategy for flexible job shop scheduling problem with the consideration of energy consumption and weight 期刊论文 Machines, 2021, 卷号: 9, 期号: 12, 页码: 1-24 作者: Wu, Mingliang; Yang DS(杨东升); Zhou BW(周博文); Yang ZL(杨之乐); Liu, Tianyi 收藏 \| 浏览/下载：17/0 \| 提交时间：2022/01/13 Dual control strategy Energy consumption Flexible job shop scheduling problem Makespan NSGA-III
	Two strategy cooperative particle swarm optimization algorithm with independent parameter adjustment and its application 期刊论文 International Journal of Innovative Computing, Information and Control, 2020, 卷号: 16, 期号: 4, 页码: 1203-1223 作者: Zhang, Qiwen; Wei, Yachen; Song, Weiyang 收藏 \| 浏览/下载：8/0 \| 提交时间：2020/11/14 Job shop scheduling Learning algorithms Parameter estimation Convergence analysis Cooperative particle swarm optimizations Differential mutations Exploitation and explorations Flexible job-shop scheduling problem Independent parameters Pre-mature convergences Standard test functions
	A Two-Phase Meta-Heuristic for Multiobjective Flexible Job Shop Scheduling Problem With Total Energy Consumption Threshold 期刊论文 IEEE Transactions on Cybernetics, 2019, 卷号: 49, 期号: 3, 页码: 1097-1109 作者: Lei, Deming*; Li, Ming; Wang, Ling 收藏 \| 浏览/下载：15/0 \| 提交时间：2019/12/04 Energy consumption threshold flexible job shop scheduling problem (FJSP) imperialist competitive algorithm (ICA) two-phase meta-heuristic (TPM) variable neighborhood search (VNS)
	An Adaptive Multi-population Artificial Bee Colony Algorithm for Multi-objective Flexible Job Shop Scheduling Problem 会议论文 Nanchang, China, June 3-5, 2019 作者: Cao Y(曹阳); Shi HB(史海波) 收藏 \| 浏览/下载：22/0 \| 提交时间：2019/11/13 multi-objective flexible job shop scheduling problem artificial bee colony algorithm multiple subpopulation
	An improved hybrid quantum particle swarm optimization algorithm for FJSP 会议论文 Zhuhai, China, February 22, 2019 - February 24, 2019 作者: Zhang, Qiwen; Hu, Songqi 收藏 \| 浏览/下载：9/0 \| 提交时间：2020/11/15 Iterative methods Particle swarm optimization (PSO) Scheduling Elitist strategies FJSP Flexible job-shop scheduling problem Neighborhood search Quantum particle swarm optimization Quantum particle swarm optimization algorithm Quantum probability amplitude Quantum-behaved Particle Swarm Optimization algorithms
	An Adaptive Multi-population Artificial Bee Colony Algorithm for Multi-objective Flexible Job Shop Scheduling Problem 会议论文 Nanchang, China, June 3-5, 2019 作者: Cao Y(曹阳); Shi HB(史海波) 收藏 \| 浏览/下载：10/0 \| 提交时间：2019/11/13 multi-objective flexible job shop scheduling problem artificial bee colony algorithm multiple subpopulation
	An Efficient Meta-Heuristic for Multi-Objective Flexible Job Shop Inverse Scheduling Problem 期刊论文 IEEE ACCESS, 2018, 卷号: 6, 页码: 59515-59527 作者: Wu, Rui; Li, Yibing*; Guo, Shunsheng; Li, Xixing 收藏 \| 浏览/下载：31/0 \| 提交时间：2019/12/04 Flexible job shop inverse scheduling problem inverse optimization multi-objective optimization multi-objective evolutionary algorithm based on decomposition particle swarm optimization
	An effective hybrid algorithm for multi-objective flexible job-shop scheduling problem 期刊论文 ADVANCES IN MECHANICAL ENGINEERING, 2018, 卷号: 10 作者: Huang, Xiabao; Guan, Zailin; Yang, Lixi 收藏 \| 浏览/下载：7/0 \| 提交时间：2019/11/21 multi-objective optimization particle swarm optimization Flexible job-shop scheduling problem hybrid algorithm genetic algorithm
	A new double flexible job-shop scheduling problem integrating processing time, green production, and human factor indicators 期刊论文 Journal of Cleaner Production, 2018, 卷号: Vol.174, 页码: 560-576 作者: Gong, GL; Deng, QW; Gong, XR; Liu, W; Ren, QH 收藏 \| 浏览/下载：3/0 \| 提交时间：2019/12/26 Double flexible job shop scheduling problem Green production indicators Human factors Multi-objective optimization Hybrid genetic algorithm

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