Testing the Primal-Dual Interior Point Method for Nonlinear Optimization Problems
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This is a test program designed to solve nonlinear optimization problems using the primal-duual interior point method. The algorithm employs iterative updates to approach the optimal solution while ensuring both convergence accuracy and computational efficiency. Key implementation features include a predictor-corrector mechanism for step size control and a barrier function to handle inequality constraints. The program efficiently addresses various nonlinear optimization challenges such as function minimization in optimization algorithms and data fitting problems, delivering precise optimal solutions. Additionally, the code architecture supports high extensibility and flexibility, allowing customization through parameter tuning and constraint modification for enhanced optimization performance. With well-structured Newton iteration loops and adaptive tolerance settings, this program serves as a practical and high-performance tool for nonlinear optimization tasks.
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