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We also consider the problem of packing maximum number k of pairwise edge-disjoint arborescences so that their union satisfies weighted degree constraints, and give an algorithm that computes a solution of value at least ⌊k/36⌋.
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In contrast, we present an algorithm that computes a direct solution of the CME.
Our algorithm computes a solution of optcost≤2⋅, so that the weighted degree of every v∈V is at most: 7b v) for arbitrary f and 5b v) for a 0,1-valued f; 2b v +4 for arbitrary f and 2b v +2 for a 0,1-valued f in the case of unit weights.
Another algorithm computes a solution of optcost≤3⋅ and weighted degrees≤6b v).
C ass computes a solution for each biconnected component separately.
Metaheuristic methods are becoming one of the important tools for producing robust and efficient methods that compute approximate solutions of problems with high quality in reasonable computation time.
We provide a formulation of the FlexRay scheduling problem that computes the optimal solution with respect to the number of additional delays when a flow-preserving implementation is not possible.
Notice that computing an approximate solution makes things easier.
To handle multiobjective optimization problems with different search techniques at each level, we hybridize an evolutionary algorithm that computes the front of Pareto optimal solutions at the lower level(s) with a gradient-based method at the upper level, for the purpose of refinement through local search.
Step 2. Compute a solution of the following subproblem: (3.1).
The algorithm used is the same split-step semi-implicit Crank Nicolson method as in the previous version (Kishor Kumar et al., 2015), which is here implemented as a series of CUDA kernels that compute the solution on the GPU.
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CEO of Professional Science Editing for Scientists @ prosciediting.com