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Both the stiffeners and their basic structures are optimized by solving two kinds of optimization problems.
To get the ϵ-solution (approximate solution), many authors have established ϵ-optimality conditions and ϵ-duality theorems for several kinds of optimization problems [1 7].
After this, by the gap function, the equivalence between two kinds of optimization problems is obtained.
Therefore, the GA can be applied for many kinds of optimization problems.
Secondly, users can also customize different kinds of optimization for 3-D molecular structure information.
Considering all papers, all kinds of optimization algorithms were used to solve problems related to Testing.
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So the scarcity of on-chip storage compared to off-chip capabilities imposes different kinds of optimizations.
However, there are algorithms that can be used to provide a near optimal solution for this kind of optimization problem.
The first is that our own intelligence is an evolved biological solution to a kind of optimization problem, operating under very tight constraints of time, energy, raw materials, historical starting point and no doubt many other factors.
McGeoch and her collaborator, Cong Wang, suggested that for at least one important kind of "optimization" problem closely related to the famed travelling-salesman problem, in which one tries to calculate the optimal path for a complicated route D-Wave's proute D-Wavenificantly outperformed conventional machines.
McGeoch and her collaborator, Cong Wang, suggested that for at least one important kind of "optimization" problem — closely related to the famed travelling-salesman problem, in which one tries to calculate the optimal path for a complicated route — D-Wave's prototype significantly outperformed conventional machines.
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