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LINEAR AND NON LINEAR OPTIMIZATION USING MATLAB

LINEAR AND NON LINEAR OPTIMIZATION USING MATLAB in Franklin, TN

Current price: $29.99
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LINEAR AND NON LINEAR OPTIMIZATION USING MATLAB

Barnes and Noble

LINEAR AND NON LINEAR OPTIMIZATION USING MATLAB in Franklin, TN

Current price: $29.99
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This book develops numerical computation and optimisation methods across examples an exercices. MATLAB can be used as a high-level programming language that includes data structures, functions, control-flow instructions, input/output handling and even object-oriented programming. MATLAB programming methods allow numerical computational techniques to be tackled through the simple implementation of theoretical algorithms that solve a wide range of problems (equations, systems, derivatives, integrals, differential equations,..). Among these problems, the solution of non-linear equations plays an important role. On the other hand, MATLAB Optimization Toolbox provides functions to search for parameters that minimise or maximise objectives while satisfying constraints. The toolbox includes solvers for linear programming (LP), mixed integer linear programming (MILP), quadratic programming (QP), second order cone programming (SOCP), nonlinear programming (NLP), constrained linear least squares, nonlinear least squares and nonlinear equations.
This book develops numerical computation and optimisation methods across examples an exercices. MATLAB can be used as a high-level programming language that includes data structures, functions, control-flow instructions, input/output handling and even object-oriented programming. MATLAB programming methods allow numerical computational techniques to be tackled through the simple implementation of theoretical algorithms that solve a wide range of problems (equations, systems, derivatives, integrals, differential equations,..). Among these problems, the solution of non-linear equations plays an important role. On the other hand, MATLAB Optimization Toolbox provides functions to search for parameters that minimise or maximise objectives while satisfying constraints. The toolbox includes solvers for linear programming (LP), mixed integer linear programming (MILP), quadratic programming (QP), second order cone programming (SOCP), nonlinear programming (NLP), constrained linear least squares, nonlinear least squares and nonlinear equations.

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