Table 3 Lower and upper bounds of the decision variables in the multiobjective optimization problem.
From: Integrating regression and multiobjective optimization techniques to analyze scientific perception
Description | Decision variable | Type | Lower bound (\(l_i\)) | Upper bound (\(u_i\)) |
|---|---|---|---|---|
Books | \(x_{1}\) | Binary | 0 | 1 |
Radio | \(x_{2}\) | Binary | 0 | 1 |
Other means | \(x_{3}\) | Binary | 0 | 1 |
Benefits of S&T equal to damages | \(x_{4}\) | Binary | 0 | 1 |
Benefits of S&T less than damages | \(x_{5}\) | Binary | 0 | 1 |
Successful statements about S&T | \(x_{6}\) | Continuous | 0 | 6 |
No financial support for science | \(x_{7}\) | Binary | 0 | 1 |
No possibilities to support science | \(x_{8}\) | Binary | 0 | 1 |
Scores to scientific techniques | \(x_{9}\) | Continuous | 0 | 5 |
Scores to social science techniques | \(x_{10}\) | Continuous | 0 | 5 |
Scores to pseudoscience techniques | \(x_{11}\) | Continuous | 0 | 5 |
Political ideology | \(x_{12}\) | Continuous | 1 | 10 |
Second level studies | \(x_{13}\) | Binary | 0 | 1 |
University studies | \(x_{14}\) | Binary | 0 | 1 |
High/very high S&T knowledge | \(x_{15}\) | Binary | 0 | 1 |
Non-catholic religion | \(x_{16}\) | Binary | 0 | 1 |
Atheist, agnostic or indifferent | \(x_{17}\) | Binary | 0 | 1 |
Labourers | \(x_{18}\) | Binary | 0 | 1 |
Small entrepreneurs, technicians and middle managers | \(x_{19}\) | Binary | 0 | 1 |
Directors and professionals | \(x_{20}\) | Binary | 0 | 1 |
Woman | \(x_{21}\) | Binary | 0 | 1 |
Income (st) | \(x_{22}\) | Continuous | − 1.112 | 5.167 |
