Journal Article
The maximization of an objective function is a cornerstone of OR/MS modeling. How can we integrate subjective values within these models without weakening their scientific objectivity?
This paper proposes a methodological answer that maintains the objective function and relaxes the maximization principle.
The authors introduce a class of biased models that combine an objective function with a “subjective” factor that biases the maximization of such a function. The authors present the main properties of these models as well as the axiomatic foundations that allow for the rigorous measurement of biasing factors.
The authors invite OR/MS scholars to participate in the development of practical applications integrating ethical and sustainability values.
Faculty
Affiliate Professor of Decision Sciences
Emeritus Professor of Technology and Operations Management