Applications – Science and Engineering

A computational study of the use of an optimization-based method for simulating large multibody systems

Categories Mechanical Engineering, Quadratic Programming

The present work aims at comparing the performance of several quadratic programming (QP) solvers for simulating large-scale frictional rigid-body systems. Traditional time-stepping schemes for simulation of multibody systems are formulated as linear complementarity problems (LCPs) with copositive matrices. Such LCPs are generally solved by means of Lemketype algorithms and solvers such as the PATH solver … Read more

Asymptotic almost-equivalence of abstract evolution systems

Categories Basic Sciences Applications, Convex and Nonsmooth Optimization Tags , ,

We study the asymptotic behavior of almost-orbits of abstract evolution systems in Banach spaces with or without a Lipschitz assumption. In particular, we establish convergence, convergence in average and almost-convergence of almost-orbits both for the weak and the strong topologies based on the behavior of the orbits. We also analyze the set of almost-stationary points. … Read more

Asymptotic equivalence and Kobayashi-type estimates for nonautonomous monotone operators in Banach spaces

Categories Basic Sciences Applications Tags , ,

We provide a sharp generalization to the nonautonomous case of the well-known Ko\-ba\-yashi estimate for proximal iterates associated with maximal monotone operators. We then derive a bound for the distance between a continuous-in-time trajectory, namely the solution to the differential inclusion $\dot{x} + A(t)x\ni 0$, and the corresponding proximal iterations. We also establish continuity properties … Read more

Strong asymptotic convergence of evolution equations governed by maximal monotone operators

Categories Applications - Science and Engineering, Convex and Nonsmooth Optimization Tags , ,

We consider the Tikhonov-like dynamics $-\dot u(t)\in A(u(t))+\varepsilon(t)u(t)$ where $A$ is a maximal monotone operator and the parameter function $\eps(t)$ tends to 0 for $t\to\infty$ with $\int_0^\infty\eps(t)dt=\infty$. When $A$ is the subdifferential of a closed proper convex function $f$, we establish strong convergence of $u(t)$ towards the least-norm minimizer of $f$. In the general case … Read more

General algorithmic frameworks for online problems

Categories Basic Sciences Applications, Convex Optimization Tags , , , , ,

We study general algorithmic frameworks for online learning tasks. These include binary classification, regression, multiclass problems and cost-sensitive multiclass classification. The theorems that we present give loss bounds on the behavior of our algorithms that depend on general conditions on the iterative step sizes. CitationInternational Journal of Pure and Applied Mathematics, Vol. 46 (2008), pp. … Read more

Passenger Name Record Data Mining Based Cancellation Forecasting for Revenue Management

Categories Data-Mining, Yield Management Tags , , , ,

Revenue management (RM) enhances the revenues of a company by means of demand-management decisions. An RM system must take into account the possibility that a booking may be canceled, or that a booked customer may fail to show up at the time of service (no-show). We review the Passenger Name Record data mining based cancellation … Read more

Accelerated line-search and trust-region methods

Categories Applications - Science and Engineering, Unconstrained Optimization Tags , , ,

In numerical optimization, line-search and trust-region methods are two important classes of descent schemes, with well-understood global convergence properties. Here we consider “accelerated” versions of these methods, where the conventional iterate is allowed to be replaced by any point that produces at least as much decrease in the cost function as a fixed fraction of … Read more

Concave programming for minimizing the zero-norm over polyhedral sets

Categories Constrained Nonlinear Optimization, Data-Mining Tags , ,

Given a non empty polyhedral set, we consider the problem of finding a vector belonging to it and having the minimum number of nonzero components, i.e., a feasible vector with minimum zero-norm. This nonsmooth combinatorial optimization problem is NP-Hard and arises in various fields such as machine learning, pattern recognition, signal processing. We propose two … Read more