Finding the strongest stable massless column with a follower load and relocatable concentrated masses

We consider the problem of optimal placement of concentrated masses along a massless elastic column that is clamped at one end and loaded by a nonconservative follower force at the free end. The goal is to find the largest possible interval such that the variation in the loading parameter within this interval preserves stability of … Read more

Split Bregman iteration for multi-period mean variance portfolio optimization

This paper investigates the problem of defining an optimal long-term investment strategy, where the investor can exit the investment before maturity without severe loss. Our setting is a multi-period one, where the aim is tomake a plan for allocating all of wealth among the n assets within a time horizon of m periods. In addition, … Read more

Accuracy and fairness trade-offs in machine learning: A stochastic multi-objective approach

In the application of machine learning to real life decision-making systems, e.g., credit scoring and criminal justice, the prediction outcomes might discriminate against people with sensitive attributes, leading to unfairness. The commonly used strategy in fair machine learning is to include fairness as a constraint or a penalization term in the minimization of the prediction … Read more

Spatially Adaptive Regularization in Image Segmentation

We modify the total-variation-regularized image segmentation model proposed by Chan, Esedoglu and Nikolova [SIAM Journal on Applied Mathematics 66, 2006] by introducing local regularization that takes into account spatial image information. We propose some techniques for defining local regularization parameters, based on the cartoon-texture decomposition of the given image, on the mean and median filters, … Read more

An Orthogonalization-free Parallelizable Framework for All-electron Calculations in Density Functional Theory

All-electron calculations play an important role in density functional theory, in which improving computational efficiency is one of the most needed and challenging tasks. In the model formulations, both nonlinear eigenvalue problem and total energy minimization problem pursue orthogonal solutions. Most existing algorithms for solving these two models invoke orthogonalization process either explicitly or implicitly … Read more

Power to Air-transportation via Hydrogen

This paper proposes a framework to analyze the concept of power to hydrogen (P2H) for fueling the next generation of aircraft. The impact of introducing new P2H loads is investigated from different aspects namely, cost, carbon emission, and wind curtailment. The newly introduced electric load is calculated based on the idea of replacing the busiest … Read more

LQR Design under Stability Constraints

The solution of classic discrete-time, finite-horizon linear quadratic regulator (LQR) problem is well known in literature. By casting the solution to be a static state-feedback, we propose a new method that trades off low LQR objective value with closed-loop stability. CitationTo appear on the special issue on the 21st IFAC World Congress 2020, IFAC PapersOnLine.ArticleDownload … Read more

Exact Penalty Function for L21 Norm Minimization over the Stiefel Manifold

L21 norm minimization with orthogonality constraints, feasible region of which is called Stiefel manifold, has wide applications in statistics and data science. The state-of-the-art approaches adopt proximal gradient technique on either Stiefel manifold or its tangent spaces. The consequent subproblem does not have closed-form solution and hence requires an iterative procedure to solve which is … Read more

Tutorials on Advanced Optimization Methods

This material provides thorough tutorials on some optimization techniques frequently used in various engineering disciplines, including convex optimization, linearization technique and mixed-integer linear programming, robust optimization, and equilibrium/game problems. It discusses how to reformulate a difficult problem to a solver-compatible form via convexi cation, linearization, and decomposition, so the original problem can be reliably solved by … Read more

Benders decomposition for Network Design Covering Problems

We consider two covering variants of the network design problem. We are given a set of origin/destination(O/D) pairs and each such O/D pair is covered if there exists a path in the network from the origin to the destination whose length is not larger than a given threshold. In the first problem, called the maximal … Read more