An Augmented Lagrangian Algorithm for Engineering Optimization by Solving Nonlinear Programming Problem

Syed Anayet Karim, MAMUN -OR- RASHID

Abstract


Augmented Lagrangian method is one of the algorithms in a class of methods for constraint optimization that seeks a solution by replacing the original constrained problems by a sequence of unconstrained subproblems. In this paper, we would like to discuss the real-world applications in the field of engineering optimization with the help of Augmented Lagrangian Algorithm (ALA) in nonlinear programming (NLP) problem. This problem is formulated as a constraint NLP and solved using updated ALA. It covers the fields of engineering which is commonly used in the optimal design. An iterative process consisting of ALA optimization also introduced with some numerical results. We use the optimality criteria with equality and inequality constraints and then employed to obtain an optimal feasible solution of the problem. These optimality criteria introduced with constraint qualification in Karush– Kuhn–Tucker conditions.

Aus. J. Bus. Sco S. & IT. Vol 4(4), October 2018, P 167-176

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