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The proposed design formulation is applied to compliance minimisation problems.
The Nelder Mead simplex method is then used to solve the minimisation problems.
Mathematical programming techniques have been widely used to solve water minimisation problems.
Dynamic programming is a powerful method for solving energy minimisation problems in computer vision, for example stereo disparity computations.
The form-finding of tensegrities is formulated as two unconstrained minimisation problems where their objective functions are defined based on eigenvalues of a modified force density matrix.
Nonconvex minimisation problems are encountered in many applications such as phase transitions in solids or liquids but also in optimal design tasks or micromagnetism.
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The determination of the disparity map is formulated as a minimisation problem in which we look to minimise the overall matching costs between corresponding pixels.
The optimality conditions of the resulting minimisation problem represent in particular a linear complementarity problem.
Like the SSA (1-layer model), the multilayer model can be reformulated as a minimisation problem.
The constrained minimisation problem is discretised using Galerkin's method, and solved using Lagrange multipliers.
In contrast, less work has been done on the water minimisation problem for batch process systems.
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