The Projected Subgradient Algorithm in Convex Optimization

The book "The Projected Subgradient Algorithm in Convex Optimization" by Alexander J. Zaslavski offers a comprehensive analysis of subgradient algorithms for solving constrained minimization problems in a Hilbert space. It is aimed at professionals engaged in the application of optimization in engineering and economics. The focus is on achieving a good approximate solution while considering computational errors that may occur during iterations. The discussion includes the various computational errors that arise at different stages of the algorithm and illustrates how these affect the quality of the solution. The book is particularly valuable as it provides solutions to a range of complex and interesting problems in numerical optimization. The subgradient-based projection algorithm is highlighted as one of the central tools in optimization theory and its applications.