Reinforcement learning based multi objective task scheduling for energy efficient and cost effective cloud edge computing. [PDF]
Zhang W, Ou H.
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CRFTS: a cluster-centric and reservation-based fault-tolerant scheduling strategy to enhance QoS in cloud computing. [PDF]
Mushtaq SU +5 more
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Collaborative optimization of layout and cutting scheduling for large-scale customized metal structural parts. [PDF]
Meng R +7 more
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A New Framework for Job Shop Integrated Scheduling and Vehicle Path Planning Problem. [PDF]
Li R, Mao J, Wu X, Zhou W, Qian C, Du H.
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Load balancing for cloud computing using optimized cluster based federated learning. [PDF]
Chennam KK +6 more
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An Effective QoS-Aware Hybrid Optimization Approach for Workflow Scheduling in Cloud Computing. [PDF]
Cui M, Wang Y.
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Dynamic multi objective task scheduling in cloud computing using reinforcement learning for energy and cost optimization. [PDF]
Yu X, Mi J, Tang L, Long L, Qin X.
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Efficient workflow scheduling using an improved multi-objective memetic algorithm in cloud-edge-end collaborative framework. [PDF]
Cui G, Zhang W, Xu W, Bao H.
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Smart load balancing in cloud computing: Integrating feature selection with advanced deep learning models. [PDF]
Sanjalawe Y +5 more
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GA-HPO PPO: A Hybrid Algorithm for Dynamic Flexible Job Shop Scheduling. [PDF]
Zhou Y +6 more
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