2015. "Enhancing the Minimization of Boolean and Multivalue Output Functions With eQMC" Journal of Mathematical Sociology 39(2):92-108. DOI: 10.1080/0022250X.2014.897949.Enhancing the minimization of Boolean and multi-value output functions with eQMC. Journal of Mathematical Sociology 39(2):92-...
Number of bins and maximum lateness minimization in two-dimensional bin packing European Journal of Operational Research, 291 (1) (2021), pp. 101-113, 10.1016/j.ejor.2020.09.023 URL: https://www.sciencedirect.com/science/article/pii/S0377221720308274 View in ScopusGoogle Scholar Asta et al....
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A simple and computationally effective method is suggested for the minimization of the switching functions that also include don''t care terms. The method is based upon the use of Boolean matrix representation of the function. The procedure is suitable for large variable functions, for computer ...
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With this approximation, the computation of μ̃k(xk) involves the minimization of the aggregated cost over a limited lookahead horizon of ℓ stages followed by the cost-to-go Jk+ℓ,π of the base policy π. In other words, this approximation assumes that the base policy takes control...
The main focus of the authors in [25] is on the minimization of execution latency, while battery life of MT, energy consumption, and optimal division of application are not taken into account. In [26, 27], the authors consider metrics such as subtask energy consumption, MT’s remaining ...
6.1. Attack Graph Analysis Method Based on Cost Minimization Algorithm For a particular network, finding the least cost in network optimization is an NP-complete problem. Cost minimization algorithms simultaneously take the vulnerability exploitation, the time spent, and economic cost into account. ...
Here, the authors propose a new algorithm for minimization and total variance applications. It is treated as a very fast method and can be used to solve the challenges in noise reduction and zooming, in addition to ensuring better proof of convergence. 2.2.4. Low-Light Image Enhancement via ...
Compressed sensing theory shows that minimization of ℓ1-norm of the absolute values of vector element is the optimal convex approximation of minimization of the ℓ0-norm. The ℓ1-norm sparse optimization model is: min||𝐶||1 min||C||1 (8) 𝑠.𝑡. 𝑌=𝑌𝐶, 𝑑𝑖...