Optimization Toolbox 6.0 - The MathWorks - #5

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Optimization Toolbox 6.0 table.main {} tr.row {} td.cell {} div.block {} div.paragraph {} .font0 { font:5.00pt "Arial", sans-serif; } .font1 { font:7.00pt "Arial", sans-serif; } .font2 { font:9.00pt "Arial", sans-serif; } .font3 { font:8.00pt "Times New Roman", serif; } .font4 { font:15.00pt "Times New Roman", serif; } ■ Finite différence of gradients, without requiring knowledge of sparsity structure For the trust-region reflective algorithm, you can use: ■ Finite difference of gradients, Hessian with known sparsity structure ■ Actual Hessian (sparse or dense) ■ Hessian-multiply function Additionally, the interior point and trust-region reflective algorithms enable you to calculate Hessian-times-vector products in a function without having to form the Hessian matrix explicitly. Optimization Toolbox also includes an interface to Ziena Optimization's ] constrained nonlinear optimization problems. libraries for solving Constrained nonlinear programming used to design an optimal suspension system. Multiobjective Optimization Multiobjective optimization is concerned with the minimization of multiple objective functions that are subject to a set of constraints. Optimization Toolbox provides functions for solving two formulations of multiobjective optimization problems: ■ The goal attainment problem involves reducing the value of a linear or nonlinear vector function to attain the goal values given in a goal vector. The relative importance of the goals is indicated using a weight vector. The goal attainment problem may also be subject to linear and nonlinear constraints. MathWorks- Accelerating the pace of engineering and science 5