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Improvement of energy efficiency of the most consuming facilities was achieved by improving the use of alternative energy minimization such as reducing the heat lost of hot gases, minimizing the heat radiated through refractory linings of metallurgical furnaces, and cooling the highly thermally stressed components.
For the sake of coherence, other algorithms based on L1 minimization (such as the solution of the problem (6)) are not included in this comparative evaluation, since they are not strictly greedy (in terms of constantly growing L0).
Therefore, this paper identifies the potential opportunities of BIM for efficient C&D waste management and minimization, such as design review, 3D coordination, quantity take-off, phase planning, site utilization planning, construction system design, digital fabrication, and 3D control and planning.
However, it should not go unmentioned that there are other, useful types of "choice" functions besides maximization or minimization, such as computing score sums, full enumeration of the search space, or stochastic sampling from it.
These tools may usually accompany secondary structure prediction packages which are based on energy minimization such as Mfold [ 1] and the Vienna RNA package [ 2], both using the expanded energy rules [ 3] to predict the folding of RNA sequences.
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In general, the solution of a constrained minimization problem such as (25) by gradient descent requires gradient projection, [27, Chapter 11].
The problem in Eq. 7 can easily be solved by applying l 1norm minimization algorithm such as least-angle regression (LARS) [14].
There are also many other methods for solving constrained convex minimization problems, such as extragradient-projection method (see [3]) and so on.
In the literature, many objectives for optimizing many types of logistics networks are described: (i) minimization objectives such as cost, inventory, transportation time, environmental impact, financial risk and (ii) maximization objectives such as profit, customer satisfaction, and flexibility and robustness.
In our approach, image morphing using the CAC is performed obtaining V1 and V2 by means of an energy function minimization technique such as the multivariate Gaussian mixture model.
The first type of data fusion reconstructs the 3D surface by conducting volumetric data segmentation using global energy minimization approaches such as graph cut [6 11], level-set [12 16], or deformable models [5, 17 19].
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