As biological data volume continues to grow, sequence-based AI is poised to become the dominant discovery layer across pharma ...
GreenScale: Multi-Objective Autoscaling for SLA, Cost, and Energy Efficiency in Cloud-Native Systems
Autoscaling is the primary method to control the performance level and the cost of cloud-native systems, thereby making them ...
In engineering systems design, theoretical deterministic solutions can be hardly applied directly to real-world scenarios. Basically, this is due to manufacturing limitations and environmental ...
ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...
With this notice, Frontiers wishes to alert readers that this article has been identified as being outside the journal’s stated scope. In accordance with our publishing policies, we have initiated an ...
In the fast-evolving field of electronic systems design, engineers are under increasing pressure to deliver innovative, high-performance products within ever ...
Abstract: Dynamic multi-objective optimization problems (DMOPs) are prevalent in many practical applications and have garnered significant attention from both industry and academia, leading to the ...
In International Conference on Evolutionary Multi-objective Optimization. DOI: 10.1007/978-981-96-3538-2_9 [arXiv] The paper introduces an acquisition function for finding the Pareto front of a ...
With the increase of the scale of the micro-grid system, the optimization of microgrid power dispatching becomes a challenging issue. From the perspective of algorithm design, traditional heuristic ...
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