Covers linear, nonlinear, and combinatorial optimization for broad applicability
Includes both theoretical and computational results for a complete understanding
Explains intuition behind interior point methods for accessible learning
Provides extensive examples, proofs, and a bibliography for research and reference
Updated bibliography ensures access to the latest研究成果
Summarized by Shop
Applied Optimization: Complementarity, Sensitivity and Algorithms Jansen, B. Operations research and mathematical programming would not be as advanced today without the many advances in interior point methods during the last decade. These methods can now solve very efficiently and robustly large scale linear, nonlinear and combinatoria