Constrained Optimization With Integer And Continuous Variables Using Inexact Restoration And Projected Gradients

dc.creatorBirgin
dc.creatorErnesto G.; Lobato
dc.creatorRafael D.; Martinez
dc.creatorJose Mario
dc.date2016
dc.datejul-dez
dc.date2017-11-13T13:45:28Z
dc.date2017-11-13T13:45:28Z
dc.date.accessioned2018-03-29T06:00:07Z
dc.date.available2018-03-29T06:00:07Z
dc.identifierBulletin Of Computational Applied Mathematics. Univ Simon Bolivar, v. 4, p. 55 - 70, 2016.
dc.identifier2244-8659
dc.identifierWOS:000390044700004
dc.identifierhttp://www.compama.co.usb.ve/node/18
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/329013
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1366038
dc.descriptionInexact 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.
dc.description4
dc.description2
dc.description55
dc.description70
dc.languageEnglish
dc.publisherUniv Simon Bolivar
dc.publisherCaracas
dc.relationBulletin of Computational Applied Mathematics
dc.rightsfechado
dc.sourceWOS
dc.subjectInexact Restoration
dc.subjectMixed-integer Nonlinear Programming (niinlp)
dc.subjectProjected Gradients
dc.titleConstrained Optimization With Integer And Continuous Variables Using Inexact Restoration And Projected Gradients
dc.typeArtículos de revistas


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