Two characterizations of Pareto minima in convex multicriteria optimization

Sanjo Zlobec

Aplikace matematiky (1984)

  • Volume: 29, Issue: 5, page 342-349
  • ISSN: 0862-7940

Abstract

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Two conditions are given each of which is both necessary and sufficient for a point to be a global Pareto minimum. The first one is obtained by studying programs where each criterion appears as a single objective function, while the second one is given in terms of a "restricted Lagrangian". The conditions are compared with the familiar characterizations of properly efficient and weakly efficient points of Karlin and Geoffrion.

How to cite

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Zlobec, Sanjo. "Two characterizations of Pareto minima in convex multicriteria optimization." Aplikace matematiky 29.5 (1984): 342-349. <http://eudml.org/doc/15365>.

@article{Zlobec1984,
abstract = {Two conditions are given each of which is both necessary and sufficient for a point to be a global Pareto minimum. The first one is obtained by studying programs where each criterion appears as a single objective function, while the second one is given in terms of a "restricted Lagrangian". The conditions are compared with the familiar characterizations of properly efficient and weakly efficient points of Karlin and Geoffrion.},
author = {Zlobec, Sanjo},
journal = {Aplikace matematiky},
keywords = {optimality conditions; properly efficient point; weakly efficient point; characterization of optimality; convex multicriteria optimization; global Pareto minimum; restricted Lagrangian; optimality conditions; properly efficient point; weakly efficient point; characterization of optimality; convex multicriteria optimization; global Pareto minimum; restricted Lagrangian},
language = {eng},
number = {5},
pages = {342-349},
publisher = {Institute of Mathematics, Academy of Sciences of the Czech Republic},
title = {Two characterizations of Pareto minima in convex multicriteria optimization},
url = {http://eudml.org/doc/15365},
volume = {29},
year = {1984},
}

TY - JOUR
AU - Zlobec, Sanjo
TI - Two characterizations of Pareto minima in convex multicriteria optimization
JO - Aplikace matematiky
PY - 1984
PB - Institute of Mathematics, Academy of Sciences of the Czech Republic
VL - 29
IS - 5
SP - 342
EP - 349
AB - Two conditions are given each of which is both necessary and sufficient for a point to be a global Pareto minimum. The first one is obtained by studying programs where each criterion appears as a single objective function, while the second one is given in terms of a "restricted Lagrangian". The conditions are compared with the familiar characterizations of properly efficient and weakly efficient points of Karlin and Geoffrion.
LA - eng
KW - optimality conditions; properly efficient point; weakly efficient point; characterization of optimality; convex multicriteria optimization; global Pareto minimum; restricted Lagrangian; optimality conditions; properly efficient point; weakly efficient point; characterization of optimality; convex multicriteria optimization; global Pareto minimum; restricted Lagrangian
UR - http://eudml.org/doc/15365
ER -

References

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