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Providing an adequate level of resilience to cloud services is a challenging problem due to the complexity of the environment as well as the need for efficient solutions that could preserve cloud benefits over other solutions.
A computational model is developed for efficient solutions of electromagnetic scattering from obstacles having random surface deformations or irregularities (such as roughness or randomly-positioned bump on the surface), by combining the Monte Carlo method with the principles of transformation electromagnetics in the context of finite element method.
They established only weak duality theorems for efficient solutions.
In this paper, we introduce generalized convex duality for nondifferentiable multiobjective program for efficient solutions.
Also, many critical problems associated with the applications of OFDMA technologies in future wireless systems are still looking for efficient solutions.
We formulate Mond-Weir-type and Wolfe-type dual problems and establish weak and strong duality theorems for efficient solutions by using suitable generalized convexity conditions.
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A finite-element orthogonal collocation scheme is developed for efficient solution of the resulting particulate reactor model.
In this paper, we construct an algebraic multigrid method suitable for efficient solution of the large scale discrete strain model.
The resulting sensor placement problem is a large-scale mixed-integer nonlinear programming (MINLP) problem that requires a tailored solution approach for efficient solution.
As alternative to classical numerical solution methods which are not well suited for efficient solution, we propose a hybrid simulation algorithm in this contribution.
This method for efficient solution-phase macrocyclization is highly useful for the rapid production and screening of loop-based inhibitors of protein protein interactions.
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