Search results for "Mathematical optimization"

Isotonic regression for metallic microstructure data: estimation and testing under order restrictions

2021

Investigating the main determinants of the mechanical performance of metals is not a simple task. Already known physical inspired qualitative relations between 2D microstructure characteristics and 3D mechanical properties can act as the starting point of the investigation. Isotonic regression allows to take into account ordering relations and leads to more efficient and accurate results when the underlying assumptions actually hold. The main goal in this paper is to test order relations in a model inspired by a materials science application. The statistical estimation procedure is described considering three different scenarios according to the knowledge of the variances: known variance ra…

Hierarchical fast BEM for anisotropic time-harmonic 3-D elastodynamics

2012

The paper presents a fast boundary element method for anisotropic time-harmonic 3-D elastodynamic problems. The approach uses the hierarchical matrices format and the ACA algorithm for the collocation matrix setup and a preconditioned GMRES solver for the solution. The development of this approach for the anisotropic case presents peculiar aspects which deserve investigation and are studied in the paper leading to the employed computational strategy and its effective tuning. Numerical experiments are presented to assess the method accuracy, performances and numerical complexity. The method ensures adequate accuracy allowing remarkable reductions in computation time and memory storage.

Avoiding strange attractors in efficient parametric families of iterative methods for solving nonlinear problems

2019

[EN] Searching zeros of nonlinear functions often employs iterative procedures. In this paper, we construct several families of iterative methods with memory from one without memory, that is, we have increased the order of convergence without adding new functional evaluations. The main aim of this manuscript yields in the advantage that the use of real multidimensional dynamics gives us to decide among the different classes designed and, afterwards, to select its most stable members. Moreover, we have found some elements of the family whose behavior includes strange attractors of different kinds that must be avoided in practice. In this sense, Feigenbaum diagrams have resulted an extremely …

On Pareto optima, the Fermat-Weber problem, and polyhedral gauges

1990

This paper deals with multiobjective programming in which the objective functions are nonsymmetric distances (derived from different gauges) to the points of a fixed finite subset of ℝn. It emphasizes the case in which the gauges are polyhedral. In this framework the following result is known: if the gauges are polyhedral, then each Pareto optimum is the solution to a Fermat—Weber problem with strictly positive coefficients. We give a new proof of this result, and we show that it is useful in finding the whole set of efficient points of a location problem with polyhedral gauges. Also, we characterize polyhedral gauges in terms of a property of their subdifferential.

Filtering with dissipativity for T-S fuzzy systems with time-varying delay: Reciprocally convex approach

2013

This paper is focused on the problem of reliable filter design with strictly dissipativity for a class of discrete-time T-S fuzzy time-delay systems. Our attention is paid on the design of reliable filter to ensure a strictly dissipative performance for the filtering error system. By employing the reciprocally convex approach, a sufficient condition of dissipativity analysis is obtained for T-S fuzzy delayed systems with sensor failures. A desired reliable filter is designed by solving a convex optimization problem.

Application of Operator Splitting Methods in Finance

2016

Financial derivatives pricing aims to find the fair value of a financial contract on an underlying asset. Here we consider option pricing in the partial differential equations framework. The contemporary models lead to one-dimensional or multidimensional parabolic problems of the convection-diffusion type and generalizations thereof. An overview of various operator splitting methods is presented for the efficient numerical solution of these problems.

An Introduction to the GAMS Modeling System

2010

Principles of scatter search

2006

Scatter search is an evolutionary method that has been successfully applied to hard optimization problems. The fundamental concepts and principles of the method were first proposed in the 1970s, based on formulations dating back to the 1960s for combining decision rules and problem constraints. In contrast to other evolutionary methods like genetic algorithms, scatter search is founded on the premise that systematic designs and methods for creating new solutions afford significant benefits beyond those derived from recourse to randomization. It uses strategies for search diversification and intensification that have proved effective in a variety of optimization problems. This paper provides…

Semiparametric stochastic frontier models: A generalized additive model approach

2017

Abstract The choice of the functional form of the frontier into a stochastic frontier model is typically neglected in applications and canonical functions are usually considered. This paper introduces a semiparametric approach for stochastic frontier estimation that extends previous works based on pseudo-likelihood estimators allowing flexibility in model selection and capability of imposing monotonicity and concavity constraints. For these purposes the present work introduces a generalized additive framework that moreover permits to model the influence of contextual/environmental factors to the hypothesized production process by the relative extension given by generalized additive models f…

A Feature Rich Distance-Based Many-Objective Visualisable Test Problem Generator

2019

In optimiser analysis and design it is informative to visualise how a search point/population moves through the design space over time. Visualisable distance-based many-objective optimisation problems have been developed whose design space is in two-dimensions with arbitrarily many objective dimensions. Previous work has shown how disconnected Pareto sets may be formed, how problems can be projected to and from arbitrarily many design dimensions, and how dominance resistant regions of design space may be defined. Most recently, a test suite has been proposed using distances to lines rather than points. However, active use of visualisable problems has been limited. This may be because the ty…