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Stochastic, zero-order, population-based optimization methods are ideal for solving this class of problems.
This technique is ideal for solving the mentioned problem, since the size of its analyzed area is about 3 5 nm in the lateral plane and about 1 nm depthward [33].
Since the solution set of the fuzzy relation equations is in general a non-convex set, when it is not empty, conventional nonlinear programming methods are not ideal for solving such a problem.
ACOmi (Ant Colony Optization for mixed-integer problems) [ 30] and fSSm [ 31] are robust extensions of metaheuristics (Ant Colony optimization and Scatter Search, respectively) that enable the handling of mixed-integer variable search domains; therefore, they are ideal for solving the MINLP problem introduced in this work.
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Thus, GAs are ideal candidates for solving multi-objective optimization groundwater problems.
The DSM is an ideal formulation for solving the tactical problem under consideration.
In this paper, central discontinuous Galerkin methods are developed for solving ideal magnetohydrodynamic (MHD) equations.
New schemes are developed on triangular grids for solving ideal magnetohydrodynamic equations while preserving globally divergence-free magnetic field.
A class of high-order kinetic flux vector splitting schemes are presented for solving ideal quantum gas dynamics based on quantum statistical mechanics.
In this paper, we propose positivity-preserving discontinuous Galerkin and central discontinuous Galerkin methods for solving ideal MHD equations by following [X. Zhang, C.-W. Shu, Journal of Computational Physics 229 (2010) 8918 8934].
The FS scheme originally introduced by Roe [in: K.W. Morton, M.J. Baines (Eds.), Numerical Methods for Fluid Dynamics II, Academic Press, New York, 1982] to solve Euler equations was extended by Aslan [J. Comput. Phys. 153 (1999) 437] for solving ideal MHD equations.
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