An end-to-end data-driven optimization framework for constrained trajectories
Many real-world problems require to optimize trajectories under constraints. Classical approaches are often based on optimal control methods but require an exact knowledge of the underlying dynamics and constraints, which could be challenging or even out
Florent Dewez +3 more
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A new logarithmic penalty function approach for nonlinear constrained optimization problem [PDF]
This paper presents a new penalty function called logarithmic penalty function (LPF) and examines the convergence of the proposed LPF method. Furthermore, the LaGrange multiplier for equality constrained optimization is derived based on the first-order ...
Mansur Hassan , Adam Baharum
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Penalization of Dirichlet optimal control problems [PDF]
We apply Robin penalization to Dirichlet optimal control problems governed by semilinear elliptic equations. Error estimates in terms of the penalization parameter are stated. The results are compared with some previous ones in the literature and are checked by a numerical experiment.
Casas Rentería, Eduardo +2 more
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Regularity for the Optimal Compliance Problem with Length Penalization [PDF]
We prove some regularity results for a connected set S in the planar domain O, which minimizes the compliance of its complement O , plus its length. This problem, interpreted as to find the best location for attaching a membrane subject to a given external force f so as to minimize the compliance, can be seen as an elliptic PDE version of the average ...
Chambolle, Antonin +3 more
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A Penalization and Regularization Technique in Shape Optimization Problems [PDF]
We consider shape optimization problems, where the state is governed by elliptic partial differential equations. Using a regularization technique, unknown shapes are encoded via shape functions, turning the shape optimization into optimal control problems for the unknown functions.
Philip, P., Tiba, D.
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A Penalized Subspace Strategy for Solving Large-Scale Constrained Optimization Problems [PDF]
Many data science problems can be efficiently addressed by minimizing a cost function subject to various constraints. In this paper a new method for solving largescale constrained differentiable optimization problems is proposed. To account efficiently for a wide range of constraints, our approach embeds a subspace algorithm into an exterior penalty ...
Martin, Ségolène +2 more
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Infinite Penalization for Optimal Control Problems: An infinite‐dimensional optimization method for constrained optimization problems [PDF]
AbstractWe present results on a method for infinite dimensional constrained optimization problems. In particular, we are interested in state constrained optimal control problems and discuss an algorithm based on penalization and smoothing. The algorithm contains update rules for the penalty and the smoothing parameter that depend on the constraint ...
Martin Gugat, Michael Herty
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Novel multi-objective topology optimization method for stiffness and stress of continuum structures
In this paper, a topology optimization method combining Bi-directional Evolutionary Structural Optimization (BESO) and Fast Non-dominated Sorting Genetic Algorithm II (NSGA-II) is proposed, which is called BESO-NSGA-II.
Shuo Feng +4 more
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Partial regularity for the optimal p-compliance problem with length penalization [PDF]
42 pages, 2 figures.
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In this paper, a practical model predictive control (MPC) for tracking desired reference trajectories is demonstrated for controlling a class of nonlinear systems subject to constraints, which comprises diverse mechanical applications.
Hossam S. Abbas +4 more
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