By Dimitri P. Bertsekas,Werner Rheinboldt
The book first bargains info at the approach to multipliers for equality limited difficulties and the tactic of multipliers for inequality restricted and nondifferentiable optimization difficulties. Discussions specialise in approximation approaches for nondifferentiable and ill-conditioned optimization difficulties; asymptotically special minimization within the tools of multipliers; duality framework for the strategy of multipliers; and the quadratic penalty functionality approach. The textual content then examines designated penalty tools, together with nondifferentiable specified penalty capabilities; linearization algorithms in response to nondifferentiable special penalty features; differentiable certain penalty features; and native and international convergence of Lagrangian tools.
The booklet ponders at the nonquadratic penalty capabilities of convex programming. subject matters comprise huge scale separable integer programming difficulties and the exponential approach to multipliers; periods of penalty services and corresponding tools of multipliers; and convergence research of multiplier tools.
The textual content is a useful reference for mathematicians and researchers attracted to the Lagrange multiplier methods.
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Additional info for Constrained Optimization and Lagrange Multiplier Methods (Computer Science & Applied Mathematics)
Constrained Optimization and Lagrange Multiplier Methods (Computer Science & Applied Mathematics) by Dimitri P. Bertsekas,Werner Rheinboldt