Augmented Lagrangian and Tchebycheff approaches in multiple objective programming

Relationships between the Tchebycheff scalarization and the augmented Lagra nge multiplier technique are examined in the framework of general multiple objective programs (MOPs). It is shown that under certain conditions the Tc hebycheff method can be represented as a quadratic weighted-sums scalarizat ion of the MOP, that is, given weight values in the former, the coefficient s of the latter can be found so that the same efficient point is selected. Analysis for concave and linear MOPs is included. Resulting applications in multiple criteria decision making are also discussed.