In this work, we solve the tangent plane distance (TPD) minimization problem. This problem is a class of problems in the field of chemical engineering, and belongs to the class of constrained minimization problems (with differentiability and nonconvexity assumptions). The TPD problem is usually solved by interior point, Newton, and heuristic methods. In this work, we propose to consider a dislocation hyperbolic augmented Lagrangian algorithm (DHALA) to solve the problem, where DHALA belongs to the class of augmented Lagrangian methods. We present computational experiments, where we show that our algorithm is competitive (in terms of execution time) with respect to other augmented Lagrangian algorithm, in the resolution of the TPD problem, and obtained better solutions than approaches reported in the literature.
Keywords: Constrained optimization, convergence analysis, TPD problem, thermodynamic equilibrium, tangent plane distance minimization
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