Constrained optimization with integer and continuous variables using inexact restoration and projected gradients

Journal Title: Bulletin of Computational Applied Mathematics (Bull CompAMa) - Year 2016, Vol 4, Issue 2

Abstract

Inexact restoration (IR) is a well established technique for continuous minimization problems with constraints that can be applied to constrained optimization problems with specific structures. When some variables are restricted to be integer, an IR strategy seems to be appropriate. The IR strategy employs a restoration procedure in which one solves a standard nonlinear programming problem and an optimization procedure in which the constraints are linearized and techniques for mixed-integer (linear or quadratic) programming can be employed.

Authors and Affiliations

Ernesto G. Birgin, Rafael D. Lobato, José Mario Martínez

Keywords

Related Articles

Integrating Fuzzy Formal Concept Analysis and Rough Set Theory for the Semantic Web

Formal Concept Analysis and Rough Set Theory provide two mathematical frameworks in information management which have been developed almost independently in the past. Currently, their integration is revealing very intere...

Numerical solution for a family of delay functional differential equations using step by step Tau approximations

We use the segmented formulation of the Tau method to approximate the solutions of a family of linear and nonlinear neutral delay differential equations \begin{eqnarray} \nonumber a_1(t)y'(t) & = & y(t)[a_2(t)y(t-\ta...

Matrix completion via a low rank factorization model and an Augmented Lagrangean Succesive Overrelaxation Algorithm

The matrix completion problem (MC) has been approximated by using the nuclear norm relaxation. Some algorithms based on this strategy require the computationally expensive singular value decomposition (SVD) at each iter...

Modeling seismic wave propagation using staggered-grid mimetic finite differences

Mimetic finite difference (MFD) approximations of continuous gradient and divergence operators satisfy a discrete version of the Gauss-Divergence theorem on staggered grids. On the mimetic approximation of this integral...

(Free) Software for general partial differential equation problems in non-rectangular 2D and 3D regions

PDE2D is a general-purpose partial differential equation solver which solves very general systems of nonlinear, steady-state, time-dependent and eigenvalue PDEs in 1D intervals, general 2D regions (see Figure 1), and a w...

Download PDF file
  • EP ID EP240479
  • DOI -
  • Views 127
  • Downloads 0

How To Cite

Ernesto G. Birgin, Rafael D. Lobato, José Mario Martínez (2016). Constrained optimization with integer and continuous variables using inexact restoration and projected gradients. Bulletin of Computational Applied Mathematics (Bull CompAMa), 4(2), 55-70. https://europub.co.uk/articles/-A-240479