Modeling learning effects via successive linear programming
type: Item
instance of: scholarly article
title: Modeling learning effects via successive linear programming
zbMATH Open document ID: 0682.90077
DOI: 10.1016/0377-2217(89)90274-9
author: Terry P. Harrison
author: J. Edward Ketz
published in: European Journal of Operational Research
publication date: 1989-01-01T00:00:00Z
review text: The learning effect is given by a model of the form: \[ \max imize\quad \sum^{n_ 1}_{j=1}[(p_ j-v_ j)x_ j-\sum^{m_ 1}_{i=1}(v_ ia_{ij})x_ j^{(1+b_{ij})}]+\sum^{N}_{j=n_ 1+1}C_ jy_ j \] subject to \[ \sum^{n_ 1}_{j=1}a_{ij}x_ j^{(1+b_{ij})}+\sum^{N}_{j=n_ 1+1}a_{ij}y_ j=r_ i,\quad i=1,...,m_ 1, \] \[ \sum^{n_ 1}_{j=1}a_{ij}x_ j+\sum^{N}_{j=n_ 1+1}a_{ij}y_ j=r_ i,\quad i=m_ 1+1,...,m, \] \[ \ell^ 1_ j\leq x_ j\leq u^ 1_ j,\quad \ell^ 2_ j\leq y_ j\leq u^ 2_ j\quad for\quad all\quad j. \] The problem is solved by successive linear programming approximations. A numerical example is given.
Mathematics Subject Classification ID: 90C30
Mathematics Subject Classification ID: 65K05
Mathematics Subject Classification ID: 90C05
zbMATH DE Number: 4118172
zbMATH Keywords: learning effect
zbMATH Keywords: successive linear programming approximations
reviewed by: Morgan A. Hanson
MaRDI profile type: Publication
full work available at URL: 0377-2217(89)90274-9
OpenAlex ID: W1974168298
cites work: Successive Linear Programming at Exxon
cites work: Design and Testing of a Generalized Reduced Gradient Code for Nonlinear Programming
cites work: Nonlinear Optimization by Successive Linear Programming
cites work: Product-Mix Models When Learning Effects are Present
description: scientific article; zbMATH DE number 4118172