For large-scale problems, heuristic approaches that achieve a trade-off between execution time and planning performance, can be good enough for making planning decisions. In this paper, we design an iterative r
2015 (Garcia and Nafarrate, 2015) Agent based Independent VM migration Balance the workload to reduce the energy consumption Complexity and high monitoring overhead 2015 (Singhet al., 2015) A2LB Independent Task migration Reduce the execution and response time Elasticity is low and complexity of ...
The minimum description length principle (Section 3.1.2) requires from the learning algorithm to find a trade-off between the hypothesis’ complexity and its accuracy. A hypothesis needs to be as simple as possible and yet provide a good data model. On the other hand, the principle of multipl...
23. If our assumptions are true, then this algorithm returns T-depth-optimal circuits with space and time complexity poly(n, 25.6n, d). Under a weaker assumption, this complexity is poly(nlogn,d,25.6n). Apart from T-depth-optimal circuit synthesis algorithms for exactly ...
Section “Whale Optimization Algorithm” provides an overview of the basic WOA. Section “Whale Optimization Algorithm based on atom-like structure differential evolution” presents the content of the WOAAD algorithm. Section “Time complexity analysis of WOAAD” analyzes the time complexity of the WOA...
Accurate and real-time product demand forecasting is the need of the hour in the world of supply chain management. Predicting future product demand from hi
Hidden Markov models are widely used for genome analysis as they combine ease of modelling with efficient analysis algorithms. Calculating the likelihood of a model using the forward algorithm has worst case time complexity linear in the length of the se
where δ is the ReLU function, and are the trainable parameters, and z is the input feature maps. In order to reduce the complexity of the model and improve the generalization ability, a bottleneck structure with two FC layers is adopted. The first FC layer is used to reduce the dimension...
By theory, in the model of one-qubit quantum computation, the input state is a completely mixed state except for a single clean qubit, and only a single output qubit is measured at the end of the computing. As the authors found, the proposed results weakens the complexity assumption ...
The selection of algorithm is influenced by the complexity level of the original algorithm, the adaptive capacity to various situations, as well as their effects on the allocation optimization. There are many indicators that can estimate algorithm's performance, such as the difficulty, and accuracy ...