Comparative Analysis Of Smooth Penalty Function Algorithms In Nonlinear Inequality Constrained Optimization
Dr. Simran Thapar
Assistant Professor, Acharya Narendra Dev College, University of Delhi, India
Abstract :- In this paper the comparative analysis of the four algorithms elucidates distinct convergence behaviours and performance attributes is provided. Algorithms I and II demonstrates an accelerated convergence rate, rendering them advantageous in scenarios prioritizing expeditious optimization. Algorithm III, while exhibiting prompt stabilization, may not attain the minimal objective function value. Algorithm IV, offering a compromise between convergence speed and the final objective function value, is a viable option when a balanced approach is deemed acceptable.
Keywords :- Smooth Penalty Function, Second Order Smooth Penalty Function, Algorithms, Objective Function, Optimality Conditions
DOI link – https://doi.org/10.69758/GIMRJ/2410III02V12P0014
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